PmagPy Command Line Version

This notebook demonstrates the use of PmagPy command line scripts. Additional background and documentation can be found in the PmagPy Cookbook.

What is PmagPy?

PmagPy is a software package for analyzing paleomagnetic and rock magnetic data using Python. If you need to install Python and PmagPy locally, follow the install instructions. This notebook demonstrates the use of PmagPy functions on the command line. For examples of how to use PmagPy scripts in a Python environment, see the static version of PmagPy.ipynb or if you are running jupyter notebook, you can open it locally.

What are paleomagnetism and rock magnetism?

For information on the science of paleomagnetism and rock magnetism, see Essentials of Paleomagnetism.

Running this notebook

You are currently looking at static html, but you may want to run this notebook interactively. To do so, you'll need to first install Python and PmagPy (see the Cookbook for install instructions). You can then launch the notebook from your command line with the following commands.

cd Desktop

move_data_files.py

cd PmagPy-data

jupyter notebook

jupyter notebook will open a browser window, and you can then click on the notebook you want to run (like this one or the PmagPy_cli notebook).

Note: You only have to do the move_data_files.py command once after initial installion and then once after each update. You should make a copy of any notebook (see File menu) if you want to make any changes as each update will overwrite the standard notebooks.

Getting started

In [1]:
import os
import glob
from IPython.display import Image
import matplotlib as plt
from pmagpy import pmag
basemap_present, Basemap = pmag.import_basemap()
cartopy_present, cartopy = pmag.import_cartopy()
from pmag_env import set_env

Help

You can get more details about any program on your command line or in a notebook. There are many options available for each program, all of which are listed in each program's help message. To call up the help message, you just need to use the command line argument -h. See the examples below:

To get help within the notebook environment:

! program_name.py -h

To get help on the command line:

program_name.py -h

If you are running Windows, you may need to run:

program_name -h

Here's an example of calling up the help message for program angle.py:

In [2]:
!angle.py -h
    NAME
        angle.py

    DESCRIPTION
      calculates angle between two input directions D1,D2

    INPUT (COMMAND LINE ENTRY)
           D1_dec D1_inc D1_dec D2_inc
    OUTPUT
           angle

    SYNTAX
        angle.py [-h][-i] [command line options] [< filename]

    OPTIONS
        -h prints help and quits
        -i for interactive data entry
        -f FILE input filename
        -F FILE output filename (required if -F set)
        Standard I/O
    

Guide to PmagPy

  • the functions in this notebook are listed alphabetically so here is a handy guide by function:
  • Calculations:

    • angle.py : calculates the angle between two vectors
    • apwp.py : returns predicted paleolatitudes, directions and pole latitude/longitude from apparent polar wander paths of Besse and Courtillot (2002).
    • b_vdm.py : converts B (in microT) and (magnetic) latitude to V(A)DM (see vdm_b.py)
    • bootams.py : calculates bootstrap statistics for tensor data
    • cart_dir.py : converts cartesian coordinates (x,y,z) to declination, inclination, intensity (see dir_cart.py)
    • di_eq.py : maps declination, inclinatitions to X,Y for plotting in equal area projections
    • di_geo.py : rotates declination, inclination in specimen coordinates to geographic
    • di_rot.py : rotates directions to a coordinate system with D,I as center
    • di_tilt.py : rotates directions to stratigraphic coordinates
    • di_vgp.py : converts direction to Virtual Geomagnetic Pole (see vgp_di.py)
    • dia_vgp.py : converts direction and $\alpha_{95}$ to Virtual Geomagnetic Pole and dp,dm
    • dipole_pinc.py : calculates inclination given latitude assuming geocentric axial dipole
    • dipole_plat.py : calculates latitude given inclination assuming geocentric axial dipole
    • dir_cart.py : converts declination, inclination, intensity to cartesian coordinates (see cart_dir.py)
    • eigs_s.py : converts eigenparameters to equivalent 6 element tensor (see s_eigs.py)
    • eq_di.py : takes X,Y from equal area projection (e.g., from digitized coordinates) and converts to declination, inclination
    • fcalc.py : returns the value from an F table, given the degrees of freedom.
    • fisher.py : generates sets of directions drawn from Fisher distributions with vertical true mean
    • fishrot.py : generates sets of directions drawn from Fisher distributions with arbitrary true mean
    • gaussian.py : generates data drawn from a normal distribution
    • gobing.py : calculates Bingham statistics from a set of directions
    • gofish.py : calculates Fisher statistics from a set of directions
    • gokent.py : calculates Kent statistics from a set of directions
    • goprinc.py : calculates principal directions statistics
    • igrf.py : calculates geomagnetic field vectors for location, age given a field model (e.g., IGRF)
    • incfish.py : estimates the true mean inclination from inclination only data
    • pca.py : calculates the best-fit line or plane for demagnetization data and associated statistics
    • pt_rot.py : rotates point given finite rotation pole
    • scalc.py : calculates VGP scatter
    • s_eigs.py : takes a 6 element tensor and calculates eigen parameters (see eigs_s.py)
    • s_geo.py : rotates 6 element tensors to geographic coordinates
    • s_hext.py : calculates Hext statistics from 6 element tensors
    • s_tilt.py : rotates 6 element tensors to stratigraphic coordinates
    • squish.py: flattens inclination data given flattening factor (see unsquish.py)
    • sundec.py : calulates direction to sun for location, date, time and sun azimuth
    • tk03.py : generates sets of directions consistent with the TK03 field model
    • uniform.py : generates sets of uniformly distributed directions
    • unsquish.py : unsquishes flattened inclinations, given flattening factor (see squish.py)
    • vector_mean : calculates vector mean for sets of vectors (declination, inclination, intensity)
    • vdm_b.py : calculates intensity at given location from specified virtual dipole moment (see b_vdm.py)
    • vgp_di.py : calculates direction at given location from virtual geomagnetic pole (see di_vgp.py)
    • watsons_f.py : calculates Watson's F statistic for testing for common mean
  • Plots:

    • ani_depthplot.py : plots anisotropy data against depth in stratigraphic section (Xmas tree plots)
    • aniso_magic.py : makes plots of anisotropy data and bootstrapped confidences
    • biplot_magic.py : plots different columns against each other in MagIC formatted data files
    • chi_magic.py : plots magnetic susceptibility data in MagIC format as function of field, frequency or temperature
    • common_mean.py : graphical approach to testing two sets of directions for common mean using bootstrap
    • core_depthplot.py : plots MagIC formatted data
    • curie.py : makes plots of Curie Temperature data and provides estimates for Tc
    • dayplot_magic.py : makes Day et al. (1977) and other plots with hysteresis statistics
    • dmag_magic.py : plots remanence against demagnetization step for MagIC formatted files
    • eqarea.py and eqarea_magic.py : makes equal area projections for directions
    • eqarea_ell.py : makes equal area projections for directions with specified confidence ellipses
    • find_ei.py : finds the inclination unflattening factor that unsquishes directions to match TK03 distribution
    • fishqq.py: makes a Quantile-Quantile plot for directions against uniform and exponential distributions
    • foldtest.py & foldtest_magic.py : finds tilt correction that maximizes concentration of directions, with bootstrap confidence bounds.
    • forc_diagram.py: plots FORC diagrams for both conventional and irregular FORCs
    • hysteresis_magic.py : makes plots of hysteresis data (not FORCs).
    • irm_unmix.py : analyzes IRM acquisition data in terms of coercivity distributions
    • irmaq_magic.py : plots IRM acquistion data
    • lnp_magic.py : plots lines and planes for site level data and calculates best fit mean and alpha_95
    • lowes.py : makes a plot of the Lowe's spectrum for a geomagnetic field model
    • lowrie.py and lowrie_magic.py : makes plots of Lowrie's (1990) 3D-IRM demagnetization experiments
    • plot_cdf.py : makes a cumulative distribution plot of data
    • plotdi_a.py : makes equal are plots of directions and their $\alpha_{95}$s
    • plot_geomagia.py : makes plots from files downloaded from the geomagia website
    • plot_magic_keys.py : plots data from MagIC formatted data files
    • qqplot.py : makes a Quantile-Quantile plot for data against a normal distribution
    • qqunf.py : makes a Quantile-Quantile plot for data against a uniform distribution
    • revtest.py & revtest_magic.py : performs a bootstrap reversals test
    • thellier_magic.py : makes plots of thellier-thellier data.
    • watsons_v.py : makes a graph for Watson's V test for common mean
    • zeq.py and zeq_magic.py : makes quicky zijderveld plots for measurement data
  • Maps:

    • cont_rot.py : makes plots of continents after rotation to specified coordinate system
    • plot_mag_map.py : makes a color contour plot of geomagnetic field models
    • plot_map_pts.py : plots points on maps
    • polemap_magic.py : reads in MagIC formatted file with paleomagnetic poles and plots them
    • vgpmap_magic.py : reads in MagIC formatted file with virtual geomagnetic poles and plots them
  • Working with MagIC:

    • combine_magic.py : combines two MagIC formatted files of same type
    • grab_magic_key.py : prints out a single column from a MagIC format file
    • magic_select.py : selects data from MagIC format file given conditions (e.g., method_codes contain string)
    • download_magic.py : unpacks a contribution text file downloaded from the MagIC website
    • upload_magic.py : prepares a directory with a MagIC contribution for uploading to MagIC
    • Conversion scripts : convert many laboratory measurement formats to the MagIC data model 3 format
      • _2g_bin_magic.py : converts 2G binary files to MagIC
      • aarm_magic.py : takes a MagIC formated measurements.txt file with anisotropy of ARM data and calculates the tensors and stores in a MagIC formatted specimens.txt file.
      • atrm_magic.py : takes a MagIC formated measurements.txt file with anisotropy of TRM data and calculates the tensors and stores in a MagIC formatted specimens.txt file.
      • agm_magic.py : converts Princeton Measurements alternating gradient force magnetization (AGM) files to MagIC.
      • bgc_magic.py : convert Berkeley Geochronology Center files to MagIC.
      • cit_magic.py : convert Cal Tech format files to MagIC.
      • generic_magic.py : converts generic files to MagIC.
      • huji_magic.py : converts Hebrew University, Jerusalem, Israel files to MagIC.
      • huji_sample_magic.py : converts HUJI files to a MagIC format.
      • jr6_jr6_magic.py : converts the AGICO JR6 spinner .jr6 files to MagIC
      • jr6_txt_magic.py : converts the AGICO JR6 .txt files to MagIC
      • k15_magic.py : converts 15 measurement anisotropy of magnetic susceptibility files to MagIC.
      • ldeo_magic.py : converts Lamont-Doherty files to MagIC.
      • livdb_magic.py : converts Liverpool files to MagIC.
      • mst_magic.py : converts Curie Temperature experimental data to MagIC
      • sio_magic.py : converts Scripps Institution of Oceanography data files to MagIC
      • sufar4_magic.py : converts AGICO SUFAR program (ver.1.2.) ascii files to MagIC
      • tdt_magic.py : converts Thellier Tool files to MagIC
      • utrecht_magic.py : converts Fort Hoofddijk, Utrecht University Robot files to MagIC
      • orientation_magic.py : converts an "orient.txt" formatted file with field notebook information into MagIC formatted files
      • azdip_magic.py : converts an "azdip" formatted file to a samples.txt file format
  • other handy scripts
    • chartmaker.py : script for making chart to guide IZZI lab experiment

_2g_bin_magic.py

[notebook version]

In [3]:
!_2g_bin_magic.py -f data_files/convert_2_magic/2G_bin_magic/mn1/mn001-1a.dat 
importing  mn001-1a
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- writing measurements records to /Users/nebula/Python/PmagPy/measurements.txt
-I- 19 records written to measurements file
-I- writing specimens records to /Users/nebula/Python/PmagPy/specimens.txt
-I- 1 records written to specimens file
-I- writing samples records to /Users/nebula/Python/PmagPy/samples.txt
-I- 1 records written to samples file
-I- writing sites records to /Users/nebula/Python/PmagPy/sites.txt
-I- 1 records written to sites file
-I- writing locations records to /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 19 records written to measurements file

aarm_magic.py

[notebook version]

In [4]:
# with data model 3
if os.path.exists('data_files/aarm_magic/specimens.txt'):
    os.remove('data_files/aarm_magic/specimens.txt')
!sio_magic.py -f data_files/aarm_magic/arm_magic_example.dat -loc Bushveld -LP AF:ANI \
    -ncn 3 ac 180 -dc 50 -1 -1 -F data_files/aarm_magic/measurements.txt
!aarm_magic.py -DM 3 -WD data_files/aarm_magic/ -f measurements.txt
!cat data_files/aarm_magic/specimens.txt | head
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 126 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 7 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 7 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 1 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- writing measurements records to /Users/nebula/Python/PmagPy/data_files/aarm_magic/measurements.txt
-I- 126 records written to measurements file
7  records written to file  /Users/nebula/Python/PmagPy/data_files/aarm_magic/specimens.txt
specimen data stored in /Users/nebula/Python/PmagPy/data_files/aarm_magic/specimens.txt
tab 	specimens
aniso_ftest	aniso_ftest12	aniso_ftest23	aniso_s	aniso_s_mean	aniso_s_n_measurements	aniso_s_sigma	aniso_s_unit	aniso_tilt_correction	aniso_type	aniso_v1	aniso_v2	aniso_v3	description	experiments	method_codes	sample	specimen
1.0	0.2	1.3	0.139969 : 0.389261 : 0.470770 : 0.009580 : 0.014135 : 0.033578	1.637e-05	9	0.155646	Am^2	-1	AARM	0.476730  :    58.8  :    78.6	0.386936  :   269.1  :     9.9	0.136334  :   178.1  :     5.7	Critical F: 2.6848;Critical F12/F13: 3.4668	bg2.01:AARM	LP-AN-ARM:AE-H		bg2.01
1.0	0.0	1.7	0.143421 : 0.418835 : 0.437744 : 0.018009 : -0.000864 : 0.035844	1.417e-05	9	0.152697	Am^2	-1	AARM	0.442121  :    25.3  :    82.2	0.419912  :   266.8  :     3.7	0.137967  :   176.3  :     6.8	Critical F: 2.6848;Critical F12/F13: 3.4668	bg2.03:AARM	LP-AN-ARM:AE-H		bg2.03
1.2	0.2	1.5	0.144980 : 0.391036 : 0.463984 : -0.013284 : 0.014477 : 0.032984	1.294e-05	9	0.143014	Am^2	-1	AARM	0.469547  :    60.6  :    79.1	0.389712  :   274.3  :     9.1	0.140741  :   183.4  :     6.0	Critical F: 2.6848;Critical F12/F13: 3.4668	bg2.06:AARM	LP-AN-ARM:AE-H		bg2.06
1.4	0.5	1.3	0.128271 : 0.365758 : 0.505971 : 0.004384 : -0.008686 : 0.077693	1.369e-05	9	0.157562	Am^2	-1	AARM	0.521706  :   345.7  :    78.5	0.365522  :    88.1  :     2.5	0.112772  :   178.6  :    11.2	Critical F: 2.6848;Critical F12/F13: 3.4668	bg2.07:AARM	LP-AN-ARM:AE-H		bg2.07
0.8	0.0	1.3	0.148865 : 0.454581 : 0.396554 : -0.003869 : -0.017902 : 0.098967	1.349e-05	9	0.191916	Am^2	-1	AARM	0.464521  :   279.9  :    27.0	0.421316  :    58.5  :    55.8	0.114164  :   179.6  :    19.3	Critical F: 2.6848;Critical F12/F13: 3.4668	bg2.08:AARM	LP-AN-ARM:AE-H		bg2.08
1.5	0.3	1.8	0.139334 : 0.386335 : 0.474331 : 0.023050 : 0.018611 : -0.000837	1.772e-05	9	0.129887	Am^2	-1	AARM	0.478148  :    86.8  :    78.4	0.384671  :   264.6  :    11.6	0.137182  :   354.7  :     0.4	Critical F: 2.6848;Critical F12/F13: 3.4668	bg2.09:AARM	LP-AN-ARM:AE-H		bg2.09
1.1	0.0	1.9	0.136281 : 0.420308 : 0.443411 : -0.010600 : -0.005003 : -0.045069	1.405e-05	9	0.150853	Am^2	-1	AARM	0.450289  :   220.1  :    79.7	0.420339  :    93.1  :     6.3	0.129373  :     2.2  :     8.2	Critical F: 2.6848;Critical F12/F13: 3.4668	bg2.12:AARM	LP-AN-ARM:AE-H		bg2.12
In [5]:
# with data model 2
!sio_magic2.py -f data_files/aarm_magic/arm_magic_example.dat -loc Bushveld -LP AF:ANI \
    -F data_files/aarm_magic/aarm_measurements.txt -ncn 3 -ac 180 -dc 50 -1 -1
!aarm_magic.py -DM 2 -f data_files/aarm_magic/aarm_measurements.txt
126  records written to file  data_files/aarm_magic/aarm_measurements.txt
results put in  data_files/aarm_magic/aarm_measurements.txt
7  records written to file  /Users/nebula/Python/PmagPy/rmag_anisotropy.txt
specimen tensor elements stored in  /Users/nebula/Python/PmagPy/rmag_anisotropy.txt
7  records written to file  /Users/nebula/Python/PmagPy/rmag_results.txt
specimen statistics and eigenparameters stored in  /Users/nebula/Python/PmagPy/rmag_results.txt

agm_magic.py

[notebook version]

In [6]:
# note: example data files are in old format
!agm_magic.py -spn myspec --usr ‘‘Lima Tango‘‘ -f data_files/convert_2_magic/agm_magic/agm_magic_example.agm -u cgs -old
-I- Using online data model
-I- Using online data model
-I- writing specimens records to /Users/nebula/Python/PmagPy/myspec_specimens.txt
-I- 1 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 1 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 1 records written to sites file
-I- writing locations records to /Users/nebula/Python/PmagPy/myspec_locations.txt
-I- 1 records written to locations file
-I- writing measurements records to /Users/nebula/Python/PmagPy/myspec.magic
-I- 284 records written to measurements file
In [7]:
!angle.py -f data_files/angle/angle.dat
   75.9
  119.1
  103.7
   81.4
  120.1
  100.9
   95.1
   74.1
   78.4
  120.1
  114.4
   66.3
   85.4
   95.1
   93.8
   93.1
  105.4
   71.8
  104.0
   93.8
   93.3
   96.3
   90.1
  112.2
   90.1
  120.0
   75.3
   86.2
   85.9
   82.6
  115.5
   99.3
   65.9
   90.6
   90.5
   84.5
   93.0
   67.5
   76.8
   83.8
  128.3
   91.7
   46.9
  110.7
  103.7
   64.4
   81.9
   94.0
  121.2
   83.6
  113.7
   76.4
  113.4
   74.1
   79.4
   74.9
   90.6
   91.4
  112.7
   77.3
   77.1
   62.4
   88.4
  106.3
  100.6
  143.8
  104.9
   91.8
   96.2
   85.6
   65.6
   88.6
   75.6
   93.4
  101.3
  115.1
   86.7
   92.3
   91.9
  102.4
   78.9
   93.4
   88.1
   94.5
   77.0
  110.4
   89.2
   80.9
  100.4
   91.9
  107.1
  115.8
  111.3
  124.6
   88.1
   66.9
   99.9
   76.7
   71.4
  100.8

ani_depthplot.py

[notebook version]

In [8]:
# OSX users with pip install should use:
#!ani_depthplot_anaconda -f data_files/ani_depthplot/rmag_anisotropy.txt -fsa data_files/ani_depthplot/er_samples.txt \
#    -fb data_files/ani_depthplot/magic_measurements.txt -sav -fmt png -DM 2

!ani_depthplot.py -f data_files/ani_depthplot/rmag_anisotropy.txt -fsa data_files/ani_depthplot/er_samples.txt \
    -fb data_files/ani_depthplot/magic_measurements.txt -sav -fmt png -DM 2
#Image(filename='U1361A_ani_depthplot.png')
Using default arguments for: -F, -A, -WD, -ID, -Fsa, -Fsi, -fa, -fsum, -ds, -d, -fsp
Saved file: U1361A_ani_depthplot.png
In [9]:
# OSX users with pip install should use:
# !ani_depthplot_anaconda -DM 3 -WD data_files/ani_depthplot -sav -fmt png

os.remove('U1361A_ani_depthplot.png')
!ani_depthplot.py -DM 3 -WD data_files/ani_depthplot -sav -fmt png
Image('U1361A_ani_depthplot.png')
Using default arguments for: -f, -F, -A, -ID, -Fsa, -Fsi, -fb, -fsa, -fa, -fsum, -ds, -d, -fsp
-I- Using online data model
Saved file: U1361A_ani_depthplot.png
Out[9]:

aniso_magic.py

[notebook version]

In [10]:
!aniso_magic.py -WD data_files/aniso_magic -crd s -f sed_specimens.txt -sav -fmt png -v -d 3 0 90 -n 300
-I- Using online data model
-W- Couldn't read in samples data
-I- Make sure you've provided the correct file name
-W- Couldn't read in samples data
-I- Make sure you've provided the correct file name
Doing bootstrap - be patient
1  saved in  _g_aniso-data.png
2  saved in  _g_aniso-conf.png
3  saved in  _g_aniso-tcdf.png
4  saved in  _g_aniso-vxcdf.png
5  saved in  _g_aniso-vycdf.png
6  saved in  _g_aniso-vzcdf.png
In [11]:
Image("_g_aniso-data.png")
Out[11]:
In [12]:
Image("_g_aniso-conf.png")
Out[12]:
In [13]:
Image("_g_aniso-tcdf.png")
Out[13]:
In [14]:
Image("_g_aniso-vxcdf.png")
Out[14]:
In [15]:
Image("_g_aniso-vycdf.png")
Out[15]:
In [16]:
Image("_g_aniso-vzcdf.png")
Out[16]:

aniso_magic2.py

In [17]:
!aniso_magic2.py -f data_files/aniso_magic/dike_anisotropy.txt -gtc 110 2 -par -v -crd g \
   -F data_files/aniso_magic/rmag_results.txt -fmt png -sav -n 300
Doing bootstrap - be patient
1  saved in  Scripps Beach_g_TY__aniso-data_.png
2  saved in  Scripps Beach_g_TY__aniso-conf_.png
3  saved in  Scripps Beach_g_TY__aniso-tcdf_.png
7  records written to file  ./data_files/aniso_magic/rmag_results.txt
In [18]:
Image(filename='Scripps Beach_g_TY__aniso-tcdf_.png')
Out[18]:
In [19]:
Image(filename='Scripps Beach_g_TY__aniso-data_.png')
Out[19]:
In [20]:
Image(filename='Scripps Beach_g_TY__aniso-conf_.png')
Out[20]:
In [21]:
!apwp.py -f data_files/apwp/apwp_example.dat
   100.0    38.8   352.4    58.1    81.5   198.3

atrm_magic.py

[notebook version]

In [22]:
if os.path.exists('data_files/atrm_magic/specimens.txt'):
    os.remove('data_files/atrm_magic/specimens.txt')
!atrm_magic.py -WD data_files/atrm_magic -f atrm_measurements3.txt
!cat data_files/atrm_magic/specimens.txt | head
-W- /Users/nebula/Python/PmagPy/data_files/atrm_magic/specimens.txt is not a valid specimens file 
30  records written to file  /Users/nebula/Python/PmagPy/data_files/atrm_magic/specimens.txt
specimen data stored in /Users/nebula/Python/PmagPy/data_files/atrm_magic/specimens.txt
tab 	specimens
aniso_ftest	aniso_ftest12	aniso_ftest23	aniso_s	aniso_s_mean	aniso_s_n_measurements	aniso_s_sigma	aniso_s_unit	aniso_tilt_correction	aniso_type	aniso_v1	aniso_v2	aniso_v3	description	experiments	method_codes	sample	specimen
15.8	2.8	19.5	0.320620 : 0.340852 : 0.338528 : 0.010075 : -0.002932 : 0.027117	1.948e-08	6	0.006994	Am^2	-1	ATRM	0.358892  :    19.3  :    50.4	0.342419  :   266.5  :    17.8	0.298689  :   163.9  :    34.0	Critical F: 3.1059;Critical F12/F13: 3.8853	ak01a:ATRM	LP-AN-TRM:AE-H	ak01a	ak01a
1.8	0.2	2.5	0.351180 : 0.343893 : 0.304926 : 0.001119 : -0.000509 : -0.012140	7.400e-09	6	0.018660	Am^2	-1	ATRM	0.354313  :   186.8  :    13.8	0.343755  :    96.5  :     1.3	0.301933  :     1.3  :    76.2	Critical F: 3.1059;Critical F12/F13: 3.8853	ak01b:ATRM	LP-AN-TRM:AE-H	ak01b	ak01b
7.1	0.4	10.9	0.339590 : 0.327797 : 0.332613 : -0.027877 : 0.023913 : 0.016300	2.045e-08	6	0.013637	Am^2	-1	ATRM	0.362559  :   136.5  :     8.8	0.350488  :    33.1  :    56.2	0.286953  :   232.1  :    32.3	Critical F: 3.1059;Critical F12/F13: 3.8853	ak01c:ATRM	LP-AN-TRM:AE-H	ak01c	ak01c
3.3	0.1	5.5	0.315177 : 0.343196 : 0.341626 : -0.000310 : 0.001497 : 0.009358	1.674e-08	6	0.009116	Am^2	-1	ATRM	0.345411  :    64.4  :    54.9	0.342406  :   281.7  :    29.2	0.312183  :   181.5  :    17.7	Critical F: 3.1059;Critical F12/F13: 3.8853	ak01d:ATRM	LP-AN-TRM:AE-H	ak01d	ak01d
20.5	9.7	16.2	0.350156 : 0.345154 : 0.304690 : 0.019606 : -0.010957 : 0.012371	1.322e-08	6	0.007063	Am^2	-1	ATRM	0.367495  :    40.5  :     2.1	0.336349  :   309.4  :    27.3	0.296157  :   134.5  :    62.6	Critical F: 3.1059;Critical F12/F13: 3.8853	ak03a:ATRM	LP-AN-TRM:AE-H	ak03a	ak03a
7.9	1.5	9.4	0.344158 : 0.306198 : 0.349644 : -0.003284 : -0.020702 : 0.004837	8.963e-09	6	0.010188	Am^2	-1	ATRM	0.359991  :   313.7  :    60.5	0.342129  :   186.2  :    19.0	0.297879  :    88.3  :    21.7	Critical F: 3.1059;Critical F12/F13: 3.8853	ak03b:ATRM	LP-AN-TRM:AE-H	ak03b	ak03b
102.8	7.8	150.7	0.302977 : 0.350641 : 0.346382 : 0.002240 : -0.006580 : 0.016298	1.020e-08	6	0.002803	Am^2	-1	ATRM	0.356930  :   285.4  :    45.3	0.345867  :    69.4  :    38.6	0.297204  :   175.2  :    18.9	Critical F: 3.1059;Critical F12/F13: 3.8853	ak03c:ATRM	LP-AN-TRM:AE-H	ak03c	ak03c
12.8	4.2	12.5	0.341299 : 0.310807 : 0.347894 : 0.010964 : -0.003338 : -0.008051	2.305e-08	6	0.006057	Am^2	-1	ATRM	0.355190  :   198.9  :    50.0	0.337549  :    16.7  :    40.0	0.307261  :   107.6  :     1.0	Critical F: 3.1059;Critical F12/F13: 3.8853	ak04a:ATRM	LP-AN-TRM:AE-H	ak04a	ak04a
In [23]:
# with MagIC 2
!sio_magic2.py -f data_files/atrm_magic/atrm_magic_example.dat -loc Africa -LP T:ANI\
    -F data_files/atrm_magic/atrm_measurements.txt -ncn 1 -dc 40 -1 -1
    
!atrm_magic.py -DM 2 -f data_files/atrm_magic/atrm_measurements.txt\
   -Fa data_files/atrm_magic/trm_anisotropy.txt -Fr data_files/atrm_magic/atrm_results.txt
210  records written to file  data_files/atrm_magic/atrm_measurements.txt
results put in  data_files/atrm_magic/atrm_measurements.txt
30  records written to file  ./rmag_anisotropy.txt
specimen tensor elements stored in  ./rmag_anisotropy.txt
30  records written to file  ./rmag_results.txt
specimen statistics and eigenparameters stored in  ./rmag_results.txt

azdip_magic.py

[notebook version]

In [24]:
# MagIC 3
!azdip_magic.py -f data_files/azdip_magic/azdip_magic_example.dat -ncn 1\
   -mcd FS-FD:SO-POM -loc "Northern Iceland" -DM 3 -WD data_files/azdip_magic
        
!cat data_files/azdip_magic/samples.txt | head
Using default arguments for: -F, -A, -ID, -Fsa, -Fsi, -app
916  records written to file  /Users/nebula/Python/PmagPy/data_files/azdip_magic/samples.txt
Data saved in  /Users/nebula/Python/PmagPy/data_files/azdip_magic/samples.txt
tab 	samples
azimuth	bed_dip	bed_dip_direction	citations	dip	location	method_codes	sample	site	software_packages
183.0	5.0	59.0	This study	76.0	Northern Iceland	FS-FD:SO-POM	is001a	is001	pmagpy-4.1.5
207.0	5.0	59.0	This study	80.0	Northern Iceland	FS-FD:SO-POM	is001b	is001	pmagpy-4.1.5
192.0	5.0	59.0	This study	59.0	Northern Iceland	FS-FD:SO-POM	is001c	is001	pmagpy-4.1.5
276.0	5.0	59.0	This study	79.0	Northern Iceland	FS-FD:SO-POM	is001d	is001	pmagpy-4.1.5
198.0	5.0	59.0	This study	34.0	Northern Iceland	FS-FD:SO-POM	is001e	is001	pmagpy-4.1.5
203.0	5.0	59.0	This study	64.0	Northern Iceland	FS-FD:SO-POM	is001f	is001	pmagpy-4.1.5
230.0	5.0	59.0	This study	48.0	Northern Iceland	FS-FD:SO-POM	is001g	is001	pmagpy-4.1.5
310.0	5.0	59.0	This study	56.0	Northern Iceland	FS-FD:SO-POM	is001h	is001	pmagpy-4.1.5
In [25]:
# MagIC 2.5
!azdip_magic.py -f data_files/azdip_magic/azdip_magic_example.dat -ncn 1\
   -mcd FS-FD:SO-POM -loc "Northern Iceland" -Fsa data_files/azdip_magic/er_samples.txt -DM 2
        
! cat data_files/azdip_magic/er_samples.txt | head
Using default arguments for: -F, -A, -WD, -ID, -Fsi, -app
916  records written to file  /Users/nebula/Python/PmagPy/data_files/azdip_magic/er_samples.txt
Data saved in  /Users/nebula/Python/PmagPy/data_files/azdip_magic/er_samples.txt
tab 	er_samples
er_citation_names	er_location_name	er_sample_name	er_site_name	magic_method_codes	magic_software_packages	sample_azimuth	sample_bed_dip	sample_bed_dip_direction	sample_dip
This study	Northern Iceland	is001a	is001	FS-FD:SO-POM	pmagpy-4.1.5	183.0	5.0	59.0	76.0
This study	Northern Iceland	is001b	is001	FS-FD:SO-POM	pmagpy-4.1.5	207.0	5.0	59.0	80.0
This study	Northern Iceland	is001c	is001	FS-FD:SO-POM	pmagpy-4.1.5	192.0	5.0	59.0	59.0
This study	Northern Iceland	is001d	is001	FS-FD:SO-POM	pmagpy-4.1.5	276.0	5.0	59.0	79.0
This study	Northern Iceland	is001e	is001	FS-FD:SO-POM	pmagpy-4.1.5	198.0	5.0	59.0	34.0
This study	Northern Iceland	is001f	is001	FS-FD:SO-POM	pmagpy-4.1.5	203.0	5.0	59.0	64.0
This study	Northern Iceland	is001g	is001	FS-FD:SO-POM	pmagpy-4.1.5	230.0	5.0	59.0	48.0
This study	Northern Iceland	is001h	is001	FS-FD:SO-POM	pmagpy-4.1.5	310.0	5.0	59.0	56.0

bgc_magic.py

[notebook version]

In [26]:
!bgc_magic.py -f data_files/convert_2_magic/BGC_magic/15HHA1-2A
mag_file in bgc_magic ./data_files/convert_2_magic/BGC_magic/15HHA1-2A
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 21 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 1 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 1 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 1 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 21 records written to measurements file
In [27]:
!b_vdm.py -f data_files/b_vdm/b_vdm_example.dat
 7.159e+22
In [28]:
!bootams.py -par   -f data_files/bootams/bootams_example.dat -n 300
Doing bootstrap - be patient

tau tau_sigma V_dec V_inc V_eta V_eta_dec V_eta_inc V_zeta V_zeta_dec V_zeta_inc

0.33505 0.00021     5.3    14.7    12.5   266.2    30.1    28.5   122.2    54.4
0.33334 0.00021   124.5    61.7    19.3   244.3    13.5    24.4   340.0    22.5
0.33161 0.00024   268.8    23.6    11.9     7.8    19.8    20.3   134.8    59.2
In [29]:
!bootams.py  -f data_files/bootams/bootams_example.dat -n 300
Doing bootstrap - be patient

tau tau_sigma V_dec V_inc V_eta V_eta_dec V_eta_inc V_zeta V_zeta_dec V_zeta_inc

0.33505 0.00020     5.3    14.7    10.0   258.4    41.9    13.8   110.0    43.5
0.33334 0.00020   124.5    61.7     6.1   224.3     5.1    17.4   317.2    29.0
0.33161 0.00013   268.8    23.6    10.6   356.5     1.6    12.7    90.2    66.3
In [30]:
!cart_dir.py -f data_files/cart_dir/cart_dir_example.dat
  340.0    65.0  1.000e+00
  176.0   -55.0  1.000e+00

chartmaker.py

[notebook version]

You can't do chartmaker from within the notebook. And chi_magic.py is still a bit buggy (problem with legend and 4th plot still shows up.)

chi_magic.py

[notebook version]

In [31]:
!chi_magic.py -f data_files/chi_magic/measurements.txt -fmt png -sav
Not enough data to plot IRM-Kappa-2352
1  saved in  IRM-OldBlue-1892_temperature.png
2  saved in  IRM-OldBlue-1892_frequency.png
In [32]:
Image('IRM-OldBlue-1892_temperature.png')
Out[32]:
In [33]:
!chi_magic2.py -f data_files/chi_magic/chi_magic_example.dat -fmt png -sav
IRM-Kappa-2352 1 out of  2
IRM-OldBlue-1892 2 out of  2
Skipping susceptibitily - AC field plot as a function of temperature
1  saved in  IRM-OldBlue-1892_1.png
2  saved in  IRM-OldBlue-1892_2.png
3  saved in  IRM-OldBlue-1892_3.png
In [34]:
Image(filename='IRM-OldBlue-1892_1.png')
Out[34]:
In [35]:
Image(filename='IRM-OldBlue-1892_3.png')
Out[35]:
In [36]:
Image(filename='IRM-OldBlue-1892_2.png')
Out[36]:

cit_magic.py

[notebook version]

In [37]:
!cit_magic.py  -f data_files/convert_2_magic/cit_magic/PI47/PI47-.sam -loc "Slate Islands" \
    -spc 1 -ncn 2 -mcd "FS-FD:SO-MAG" -A 
PI47-

Warning: Specimen volume set to 1.0.
Warning: If volume/mass really is 1.0, set volume/mass to 1.001
Warning: specimen method code LP-NOMAG set.
Warning: Specimen volume set to 1.0.
Warning: If volume/mass really is 1.0, set volume/mass to 1.001
Warning: specimen method code LP-NOMAG set.
Warning: Specimen volume set to 1.0.
Warning: If volume/mass really is 1.0, set volume/mass to 1.001
Warning: specimen method code LP-NOMAG set.
Warning: Specimen volume set to 1.0.
Warning: If volume/mass really is 1.0, set volume/mass to 1.001
Warning: specimen method code LP-NOMAG set.
Warning: Specimen volume set to 1.0.
Warning: If volume/mass really is 1.0, set volume/mass to 1.001
Warning: specimen method code LP-NOMAG set.
Warning: Specimen volume set to 1.0.
Warning: If volume/mass really is 1.0, set volume/mass to 1.001
Warning: specimen method code LP-NOMAG set.
Warning: Specimen volume set to 1.0.
Warning: If volume/mass really is 1.0, set volume/mass to 1.001
Warning: specimen method code LP-NOMAG set.
Warning: Specimen volume set to 1.0.
Warning: If volume/mass really is 1.0, set volume/mass to 1.001
Warning: specimen method code LP-NOMAG set.
Warning: Specimen volume set to 1.0.
Warning: If volume/mass really is 1.0, set volume/mass to 1.001
Warning: specimen method code LP-NOMAG set.
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 266 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 9 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 9 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 1 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 266 records written to measurements file

combine_magic.py

MagIC tables have many columns only some of which are used in a particular instance. So combining files of the same type must be done carefully to ensure that the right data come under the right headings. The program combine_magic.py can be used to combine any number of MagIC files from a given type.

[notebook version]

In [38]:
!combine_magic.py -WD data_files/combine_magic -F measurements.txt -f af_measurements.txt therm_measurements.txt 
Using default arguments for: -A, -ID, -Fsa, -Fsi, -dm
-I- Using online data model
-I- Using online data model
-I- overwriting /Users/nebula/Python/PmagPy/data_files/combine_magic/measurements.txt
-I- 58 records written to measurements file

common_mean.py

In [39]:
!common_mean.py -f data_files/common_mean/common_mean_ex_file1.dat\
   -f2 data_files/common_mean/common_mean_ex_file2.dat -sav -fmt png
Doing first set of directions, please be patient..
Doing second  set of directions, please be patient..
1  saved in  CD_X.png
2  saved in  CD_Y.png
3  saved in  CD_Z.png
In [40]:
Image(filename='CD_X.png')
Out[40]:
In [41]:
Image(filename='CD_Y.png')
Out[41]:
In [42]:
Image(filename='CD_Z.png')
Out[42]:
In [258]:
!cont_rot.py -con af:sam -prj ortho\
    -eye -20 0 -sym k-  1 -age 180 -res l  -fmt png -sav
gridlines only supported for PlateCarree and Mercator plots currently
gridlines only supported for PlateCarree and Mercator plots currently
<class 'IndexError'> Out of bounds on buffer access (axis 0)
could not save:  1 Cont_rot.png
output file format not supported 
In [44]:
if basemap_present:
    image = Image(filename="Cont_rot.png")
else: 
    image = None
image

core_depthplot.py

[notebook version]

In [45]:
# OSX users with pip install should use:
#!core_depthplot_anaconda -fsa data_files/core_depthplot/er_samples.txt -LP AF 15 \
#    -f data_files/core_depthplot/magic_measurements.txt -log \
#    -d 50 150 -ts gts12 23 34 -D -fmt png -sav -DM 2

# test with MagIC 2.5
!core_depthplot.py -fsa data_files/core_depthplot/er_samples.txt -LP AF 15 \
    -f data_files/core_depthplot/magic_measurements.txt -log \
    -d 50 150 -ts gts12 23 34 -D -fmt png -sav -DM 2
Using default arguments for: -F, -A, -WD, -ID, -Fsa, -Fsi, -fsum, -fwig, -fa, -fsp, -fres, -n, -L, -S, -I, -M, -ds, -sym
9328  measurements read in from  /Users/nebula/Python/PmagPy/data_files/core_depthplot/magic_measurements.txt
using intensity key: measurement_magn_mass
2332 depths found
-I- Created plot: DSDP Site 522_m__LT-AF-Z_core-depthplot.png
In [46]:
Image(filename='DSDP Site 522_m__LT-AF-Z_core-depthplot.png')
Out[46]:
In [47]:
# OSX users with pip install should use:

#!core_depthplot_anaconda -DM 3 -fsa ./data_files/core_depthplot/samples.txt -LP AF 15 \
#    -f ./data_files/core_depthplot/measurements.txt -log \
#    -d 50 150 -ts gts12 23 34 -D -fmt png -sav -DM 3 -ID ./data_files/core_depthplot

try:
    os.remove('DSDP Site 522_m__LT-AF-Z_core-depthplot.png')
except FileNotFoundError:
    pass
!core_depthplot.py -DM 3 -fsa ./data_files/core_depthplot/samples.txt -LP AF 15 \
    -f ./data_files/core_depthplot/measurements.txt -log \
    -d 50 150 -ts gts12 23 34 -D -fmt png -sav -DM 3 -ID ./data_files/core_depthplot
Using default arguments for: -F, -A, -WD, -Fsa, -Fsi, -fsum, -fwig, -fa, -fsp, -fres, -n, -L, -S, -I, -M, -ds, -sym
-I- Using online data model
-W- Column 'composite_depth' isn't in sites table, skipping it
9328  measurements read in from  /Users/nebula/Python/PmagPy/data_files/core_depthplot/measurements.txt
using intensity key: magn_mass
2332 depths found
-I- Created plot: DSDP Site 522_m__LT-AF-Z_core-depthplot.png
In [48]:
Image('DSDP Site 522_m__LT-AF-Z_core-depthplot.png')
Out[48]:
In [49]:
# OSX users with pip install should use:
#!core_depthplot_anaconda -DM 3 -fa ./data_files/core_depthplot/ages.txt -LP AF 15 \
#    -f ./data_files/core_depthplot/measurements.txt -log \
#     -ts gts12 23 34 -D -fmt png -sav -DM 3 -ID ./data_files/core_depthplot

try:
    os.remove('DSDP Site 522_m__LT-AF-Z_core-depthplot.png')
except FileNotFoundError:
    pass
!core_depthplot.py -DM 3 -fa ./data_files/core_depthplot/ages.txt -LP AF 15 \
    -f ./data_files/core_depthplot/measurements.txt -log \
     -ts gts12 23 34 -D -fmt png -sav -DM 3 -ID ./data_files/core_depthplot # not a meaningful option with age -d 50 150
Using default arguments for: -F, -A, -WD, -Fsa, -Fsi, -fsum, -fwig, -fsa, -fsp, -fres, -n, -d, -L, -S, -I, -M, -ds, -sym
-I- Using online data model
-W- Column 'composite_depth' isn't in sites table, skipping it
-I- Adding age_high and age_low to locations table based on minimum/maximum ages found in sites table
9328  measurements read in from  /Users/nebula/Python/PmagPy/data_files/core_depthplot/measurements.txt
using intensity key: magn_mass
2332 depths found
-I- Created plot: DSDP Site 522_m__LT-AF-Z_core-depthplot.png
In [50]:
Image('DSDP Site 522_m__LT-AF-Z_core-depthplot.png')
Out[50]:
In [51]:
!curie.py -f data_files/curie/curie_example.dat -w 10 -fmt png -sav
second derivative maximum is at T=552
1  saved in  M_T.png
2  saved in  der1.png
3  saved in  der2.png
4  saved in  Curie.png
In [52]:
Image(filename='M_T.png')
Out[52]:

dayplot_magic.py

[notebook version]

In [53]:
!dayplot_magic.py -WD data_files/dayplot_magic -f specimens.txt -sav -fmt png
-I- Using online data model
1  saved in  _day.png
2  saved in  _S-Bc.png
3  saved in  _S-Bcr.png
In [54]:
Image("_day.png")
Out[54]:

dayplot_magic2.py

In [55]:
!dayplot_magic2.py -WD data_files/dayplot_magic/ -f dayplot_magic_example.dat \
    -fmt png -sav
1  saved in  unknown_day.png
2  saved in  unknown_S-Bc.png
3  saved in  unknown_S-Bcr.png
In [56]:
Image(filename='unknown_day.png')
Out[56]:

demag_gui.py

Use demag_gui.py from the command line or from within pmag_gui.py (Pmag GUI).

In [57]:
!di_eq.py -f data_files/di_eq/di_eq_example.dat
-0.239410 -0.893491
0.436413 0.712161
0.063844 0.760300
0.321447 0.686216
0.322720 0.670562
0.407412 0.540654
0.580156 0.340376
0.105351 0.657728
0.247173 0.599687
0.182349 0.615600
0.174815 0.601717
0.282746 0.545472
0.264863 0.538273
0.235758 0.534536
0.290665 0.505482
0.260629 0.511513
0.232090 0.516423
0.244448 0.505666
0.277927 0.464381
0.250510 0.477152
0.291770 0.440816
0.108769 0.516148
0.196706 0.482014
0.349390 0.381292
0.168407 0.475566
0.206286 0.446444
0.175701 0.450649
0.301104 0.378539
0.204955 0.423970
0.199755 0.422584
0.346920 0.308010
0.119030 0.441144
0.239848 0.376486
0.269528 0.342510
0.085451 0.423789
0.192224 0.387233
0.172608 0.395084
0.272008 0.320741
0.393981 0.117451
-0.017726 0.406002
0.154273 0.367000
0.213903 0.335760
0.103221 0.372202
0.231833 0.283245
0.072160 0.351538
0.007802 0.319236
0.152583 0.265350
0.248133 0.136412
In [58]:
!di_geo.py -f data_files/di_geo/di_geo_example.dat -F data_files/di_geo/di_geo.out
!cat data_files/di_geo/di_geo.out | head
data_files/di_geo/di_geo.out  opened for output
   12.4    19.0
   15.0    15.6
   10.7    18.2
   11.4    19.0
   12.4    17.2
  357.3    15.2
  353.9    21.7
  353.8    21.6
  340.5    25.3
  342.6    27.5
In [59]:
!eqarea.py -f data_files/di_rot/di_rot_example.txt -fmt png -sav
Image(filename='di_rot_example_eq.png')
1  saved in  di_rot_example_eq.png
Out[59]:
In [60]:
!di_rot.py -f data_files/di_rot/di_rot_example.txt -F data_files/di_rot/dirot.out -D 359.3 -I 42.1
!eqarea.py -f data_files/di_rot/dirot.out -fmt png -sav
1  saved in  dirot_eq.png
In [61]:
Image(filename='dirot_eq.png')
Out[61]:
In [62]:
!di_tilt.py < data_files/di_tilt/di_tilt_example.dat
   37.5    49.6
  336.5    60.9
  338.0    23.0
  355.7     7.5
    8.2    58.6
    6.2    29.8
  357.0    50.0
  342.8    58.6
  339.3     0.3
    3.9    21.7
  354.3    49.0
    0.3    48.6
  335.8    64.0
   18.1    32.8
  353.9    31.3
   30.8    48.1
   28.0    42.6
  352.8    38.6
  351.4    47.9
   15.0     5.8
  201.4   -27.4
  194.5   -60.3
  151.7   -34.4
  202.4   -54.6
  178.1    13.5
  174.2   -38.4
  192.5   -44.2
  182.4   -10.1
  187.2   -51.7
  158.1     0.5
  181.3   -36.6
  194.1   -47.0
  158.2    -7.0
  204.1   -24.0
  177.7   -36.9
  179.3   -53.7
  173.7   -27.8
  186.3    14.8
  168.9   -37.3
  168.2   -23.5
   13.3    42.3
  348.4    55.8
  353.9    54.8
    8.7    39.2
  340.0     7.0
  336.2    47.9
    3.8    25.4
   14.3    15.7
  323.9    36.7
   12.7    56.4
   14.2    51.6
  348.7    11.4
  345.1    26.8
  350.4    47.4
  352.3     7.3
    3.9    32.2
   31.9    67.9
    8.1    47.2
   32.6    48.6
   18.9     1.5
  159.5   -48.4
  164.1    -8.8
  168.1   -49.8
  173.4   -38.0
  169.6   -25.6
  201.1   -38.6
  189.2     3.2
  168.2   -22.8
  166.3   -51.6
  178.5   -26.6
  179.6   -27.0
  180.1   -29.0
  172.0   -47.0
  171.0   -38.9
  177.8   -58.0
  195.0   -25.7
  188.4   -56.8
  166.3   -27.0
  182.3   -57.6
  181.9   -40.0
In [63]:
!di_vgp.py -f data_files/di_vgp/di_vgp_example.dat
  154.7    77.3
    6.6   -69.6

dipole_pinc.py

[notebook version]

In [64]:
!dipole_pinc.py -f data_files/dipole_pinc/dipole_pinc_example.dat
  -41.7

dipole_plat.py

[notebook version]

In [65]:
!dipole_plat.py -f data_files/dipole_plat/dipole_plat_example.dat
   12.0
In [66]:
!dir_cart.py -f data_files/dir_cart/dir_cart_example.dat
8.4859e-01 3.0886e-01 9.3514e-01
-3.8223e+00 3.3441e-01 -1.7083e+00

dmag_magic.py

[notebook version]

In [67]:
!dmag_magic.py -WD data_files/3_0/McMurdo -fsp specimens.txt -obj spc -sav -fmt "png" -LT T
-I- Using online data model
25470  records read from  measurements.txt
1  saved in  mc01a_LT-T-Z.png
1  saved in  mc01b_LT-T-Z.png
1  saved in  mc01c_LT-T-Z.png
1  saved in  mc01d_LT-T-Z.png
1  saved in  mc01e_LT-T-Z.png
1  saved in  mc01g_LT-T-Z.png
1  saved in  mc01h_LT-T-Z.png
1  saved in  mc02a_LT-T-Z.png
1  saved in  mc02b_LT-T-Z.png
1  saved in  mc02f_LT-T-Z.png
1  saved in  mc02h_LT-T-Z.png
1  saved in  mc03a_LT-T-Z.png
1  saved in  mc03c_LT-T-Z.png
1  saved in  mc03f_LT-T-Z.png
1  saved in  mc03h_LT-T-Z.png
1  saved in  mc04b_LT-T-Z.png
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1  saved in  mc04f_LT-T-Z.png
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1  saved in  mc06d_LT-T-Z.png
1  saved in  mc06g_LT-T-Z.png
1  saved in  mc06h_LT-T-Z.png
1  saved in  mc07b_LT-T-Z.png
1  saved in  mc07c_LT-T-Z.png
1  saved in  mc07d_LT-T-Z.png
1  saved in  mc07f_LT-T-Z.png
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1  saved in  mc08f_LT-T-Z.png
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1  saved in  mc21e_LT-T-Z.png
1  saved in  mc21f_LT-T-Z.png
1  saved in  mc21g_LT-T-Z.png
1  saved in  mc21h_LT-T-Z.png
1  saved in  mc220a1_LT-T-Z.png
1  saved in  mc220b1_LT-T-Z.png
1  saved in  mc220c1_LT-T-Z.png
1  saved in  mc220d1_LT-T-Z.png
1  saved in  mc220e1_LT-T-Z.png
1  saved in  mc221b1_LT-T-Z.png
1  saved in  mc222b1_LT-T-Z.png
1  saved in  mc223a1_LT-T-Z.png
1  saved in  mc223b1_LT-T-Z.png
1  saved in  mc223c2_LT-T-Z.png
1  saved in  mc223g1_LT-T-Z.png
1  saved in  mc223l1_LT-T-Z.png
1  saved in  mc224b1_LT-T-Z.png
1  saved in  mc225a1_LT-T-Z.png
1  saved in  mc225b1_LT-T-Z.png
1  saved in  mc225c1_LT-T-Z.png
1  saved in  mc225d1_LT-T-Z.png
1  saved in  mc225i1_LT-T-Z.png
1  saved in  mc226b1_LT-T-Z.png
1  saved in  mc227b1_LT-T-Z.png
1  saved in  mc228a1_LT-T-Z.png
1  saved in  mc228b1_LT-T-Z.png
1  saved in  mc228d1_LT-T-Z.png
1  saved in  mc228e1_LT-T-Z.png
1  saved in  mc228g1_LT-T-Z.png
1  saved in  mc229b1_LT-T-Z.png
1  saved in  mc229g1_LT-T-Z.png
1  saved in  mc229h1_LT-T-Z.png
1  saved in  mc229i1_LT-T-Z.png
1  saved in  mc229k1_LT-T-Z.png
1  saved in  mc26a_LT-T-Z.png
1  saved in  mc26b_LT-T-Z.png
1  saved in  mc26c_LT-T-Z.png
1  saved in  mc26d_LT-T-Z.png
1  saved in  mc26e_LT-T-Z.png
1  saved in  mc26f_LT-T-Z.png
1  saved in  mc26g_LT-T-Z.png
1  saved in  mc28a_LT-T-Z.png
1  saved in  mc28b_LT-T-Z.png
1  saved in  mc28c_LT-T-Z.png
1  saved in  mc28e_LT-T-Z.png
1  saved in  mc28f_LT-T-Z.png
1  saved in  mc28g_LT-T-Z.png
1  saved in  mc28h_LT-T-Z.png
1  saved in  mc29b_LT-T-Z.png
1  saved in  mc29c_LT-T-Z.png
1  saved in  mc29d_LT-T-Z.png
1  saved in  mc29e_LT-T-Z.png
1  saved in  mc29g_LT-T-Z.png
1  saved in  mc29h_LT-T-Z.png
1  saved in  mc30a_LT-T-Z.png
1  saved in  mc30b_LT-T-Z.png
1  saved in  mc30d_LT-T-Z.png
1  saved in  mc30e_LT-T-Z.png
1  saved in  mc30f_LT-T-Z.png
1  saved in  mc30g_LT-T-Z.png
1  saved in  mc30h_LT-T-Z.png
1  saved in  mc31b_LT-T-Z.png
1  saved in  mc31c_LT-T-Z.png
1  saved in  mc31d_LT-T-Z.png
1  saved in  mc31h_LT-T-Z.png
1  saved in  mc32a_LT-T-Z.png
1  saved in  mc32b_LT-T-Z.png
1  saved in  mc32d_LT-T-Z.png
1  saved in  mc32e_LT-T-Z.png
1  saved in  mc32g_LT-T-Z.png
1  saved in  mc32h_LT-T-Z.png
1  saved in  mc33a_LT-T-Z.png
1  saved in  mc33b_LT-T-Z.png
1  saved in  mc33c_LT-T-Z.png
1  saved in  mc33e_LT-T-Z.png
1  saved in  mc33f_LT-T-Z.png
1  saved in  mc33g_LT-T-Z.png
1  saved in  mc33h_LT-T-Z.png
1  saved in  mc34a_LT-T-Z.png
1  saved in  mc34b_LT-T-Z.png
1  saved in  mc34c_LT-T-Z.png
1  saved in  mc34e_LT-T-Z.png
1  saved in  mc34f_LT-T-Z.png
1  saved in  mc34h_LT-T-Z.png
1  saved in  mc35a_LT-T-Z.png
1  saved in  mc35b_LT-T-Z.png
1  saved in  mc35c_LT-T-Z.png
1  saved in  mc35d_LT-T-Z.png
1  saved in  mc35e_LT-T-Z.png
1  saved in  mc35g_LT-T-Z.png
1  saved in  mc35h_LT-T-Z.png
1  saved in  mc36a_LT-T-Z.png
1  saved in  mc36b_LT-T-Z.png
1  saved in  mc36c_LT-T-Z.png
1  saved in  mc36d_LT-T-Z.png
1  saved in  mc36e_LT-T-Z.png
1  saved in  mc36f_LT-T-Z.png
1  saved in  mc36h_LT-T-Z.png
1  saved in  mc37a_LT-T-Z.png
1  saved in  mc37b_LT-T-Z.png
1  saved in  mc37c_LT-T-Z.png
1  saved in  mc37d_LT-T-Z.png
1  saved in  mc37e_LT-T-Z.png
1  saved in  mc37g_LT-T-Z.png
1  saved in  mc37h_LT-T-Z.png
1  saved in  mc38a_LT-T-Z.png
1  saved in  mc38c_LT-T-Z.png
1  saved in  mc38e_LT-T-Z.png
1  saved in  mc38f_LT-T-Z.png
1  saved in  mc38g_LT-T-Z.png
1  saved in  mc38h_LT-T-Z.png
1  saved in  mc39a_LT-T-Z.png
1  saved in  mc39b_LT-T-Z.png
1  saved in  mc39c_LT-T-Z.png
1  saved in  mc39d_LT-T-Z.png
1  saved in  mc39e_LT-T-Z.png
1  saved in  mc39f_LT-T-Z.png
1  saved in  mc39h_LT-T-Z.png
1  saved in  mc40a_LT-T-Z.png
1  saved in  mc40b_LT-T-Z.png
1  saved in  mc40e_LT-T-Z.png
1  saved in  mc40f_LT-T-Z.png
1  saved in  mc40g_LT-T-Z.png
1  saved in  mc40h_LT-T-Z.png
1  saved in  mc41b_LT-T-Z.png
1  saved in  mc41d_LT-T-Z.png
1  saved in  mc41e_LT-T-Z.png
1  saved in  mc41h_LT-T-Z.png
1  saved in  mc42b_LT-T-Z.png
1  saved in  mc42c_LT-T-Z.png
1  saved in  mc42d_LT-T-Z.png
1  saved in  mc42h_LT-T-Z.png
1  saved in  mc43b_LT-T-Z.png
1  saved in  mc43e_LT-T-Z.png
1  saved in  mc43f_LT-T-Z.png
1  saved in  mc43g_LT-T-Z.png
1  saved in  mc44a_LT-T-Z.png
1  saved in  mc44b_LT-T-Z.png
1  saved in  mc44c_LT-T-Z.png
1  saved in  mc44e_LT-T-Z.png
1  saved in  mc44f_LT-T-Z.png
1  saved in  mc44g_LT-T-Z.png
1  saved in  mc44h_LT-T-Z.png
1  saved in  mc48a_LT-T-Z.png
1  saved in  mc48b_LT-T-Z.png
1  saved in  mc48d_LT-T-Z.png
1  saved in  mc48e_LT-T-Z.png
1  saved in  mc48f_LT-T-Z.png
1  saved in  mc48g_LT-T-Z.png
1  saved in  mc48h_LT-T-Z.png
1  saved in  mc49b_LT-T-Z.png
1  saved in  mc49e_LT-T-Z.png
1  saved in  mc49g_LT-T-Z.png
1  saved in  mc49h_LT-T-Z.png
1  saved in  mc50a_LT-T-Z.png
1  saved in  mc50b_LT-T-Z.png
1  saved in  mc50c_LT-T-Z.png
1  saved in  mc50e_LT-T-Z.png
1  saved in  mc50f_LT-T-Z.png
1  saved in  mc50g_LT-T-Z.png
1  saved in  mc50h_LT-T-Z.png
In [68]:
Image(filename="mc01a_LT-T-Z.png")
Out[68]:
In [69]:
Image("mc141c1_LT-T-Z.png")
Out[69]:
In [70]:
!dmag_magic.py -WD data_files/3_0/McMurdo -fsp specimens.txt \
-fsa samples.txt -obj sit -sav -fmt "png" -LT T
-I- Using online data model
25470  records read from  measurements.txt
1  saved in  mc01_LT-T-Z.png
1  saved in  mc02_LT-T-Z.png
1  saved in  mc03_LT-T-Z.png
1  saved in  mc04_LT-T-Z.png
1  saved in  mc06_LT-T-Z.png
1  saved in  mc07_LT-T-Z.png
1  saved in  mc08_LT-T-Z.png
1  saved in  mc09_LT-T-Z.png
1  saved in  mc10_LT-T-Z.png
1  saved in  mc100_LT-T-Z.png
1  saved in  mc102_LT-T-Z.png
1  saved in  mc103_LT-T-Z.png
1  saved in  mc104_LT-T-Z.png
1  saved in  mc105_LT-T-Z.png
1  saved in  mc107_LT-T-Z.png
1  saved in  mc108_LT-T-Z.png
1  saved in  mc109_LT-T-Z.png
1  saved in  mc11_LT-T-Z.png
1  saved in  mc110_LT-T-Z.png
1  saved in  mc111_LT-T-Z.png
1  saved in  mc112_LT-T-Z.png
1  saved in  mc113_LT-T-Z.png
1  saved in  mc115_LT-T-Z.png
1  saved in  mc116_LT-T-Z.png
1  saved in  mc117_LT-T-Z.png
1  saved in  mc119_LT-T-Z.png
1  saved in  mc120_LT-T-Z.png
1  saved in  mc121_LT-T-Z.png
1  saved in  mc122_LT-T-Z.png
1  saved in  mc123_LT-T-Z.png
1  saved in  mc124_LT-T-Z.png
1  saved in  mc125_LT-T-Z.png
1  saved in  mc126_LT-T-Z.png
1  saved in  mc127_LT-T-Z.png
1  saved in  mc128_LT-T-Z.png
1  saved in  mc129_LT-T-Z.png
1  saved in  mc13_LT-T-Z.png
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1  saved in  mc167_LT-T-Z.png
1  saved in  mc168_LT-T-Z.png
1  saved in  mc19_LT-T-Z.png
1  saved in  mc20_LT-T-Z.png
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1  saved in  mc201_LT-T-Z.png
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1  saved in  mc220_LT-T-Z.png
1  saved in  mc221_LT-T-Z.png
1  saved in  mc222_LT-T-Z.png
1  saved in  mc223_LT-T-Z.png
1  saved in  mc224_LT-T-Z.png
1  saved in  mc225_LT-T-Z.png
1  saved in  mc226_LT-T-Z.png
1  saved in  mc227_LT-T-Z.png
1  saved in  mc228_LT-T-Z.png
1  saved in  mc229_LT-T-Z.png
1  saved in  mc26_LT-T-Z.png
1  saved in  mc28_LT-T-Z.png
1  saved in  mc29_LT-T-Z.png
1  saved in  mc30_LT-T-Z.png
1  saved in  mc31_LT-T-Z.png
1  saved in  mc32_LT-T-Z.png
1  saved in  mc33_LT-T-Z.png
1  saved in  mc34_LT-T-Z.png
1  saved in  mc35_LT-T-Z.png
1  saved in  mc36_LT-T-Z.png
1  saved in  mc37_LT-T-Z.png
1  saved in  mc38_LT-T-Z.png
1  saved in  mc39_LT-T-Z.png
1  saved in  mc40_LT-T-Z.png
1  saved in  mc41_LT-T-Z.png
1  saved in  mc42_LT-T-Z.png
1  saved in  mc43_LT-T-Z.png
1  saved in  mc44_LT-T-Z.png
1  saved in  mc48_LT-T-Z.png
1  saved in  mc49_LT-T-Z.png
1  saved in  mc50_LT-T-Z.png
In [71]:
Image(filename="mc01_LT-T-Z.png")
Out[71]:

dmag_magic2.py

In [72]:
!dmag_magic2.py -f data_files/dmag_magic/dmag_magic_example.dat -LT AF -fmt png -sav
5921  records read from  data_files/dmag_magic/dmag_magic_example.dat
1  saved in  McMurdo_LT-AF-Z.png
In [73]:
Image(filename='McMurdo_LT-AF-Z.png')
Out[73]:

download_magic.py

[notebook version]

In [74]:
!download_magic.py -WD data_files/download_magic -f data_files/download_magic/magic_contribution_16503.txt 
working on:  'contribution'
1  records written to file  data_files/download_magic/contribution.txt
contribution  data put in  data_files/download_magic/contribution.txt
working on:  'locations'
3  records written to file  data_files/download_magic/locations.txt
locations  data put in  data_files/download_magic/locations.txt
working on:  'sites'
52  records written to file  data_files/download_magic/sites.txt
sites  data put in  data_files/download_magic/sites.txt
working on:  'samples'
437  records written to file  data_files/download_magic/samples.txt
samples  data put in  data_files/download_magic/samples.txt
working on:  'specimens'
226  records written to file  data_files/download_magic/specimens.txt
specimens  data put in  data_files/download_magic/specimens.txt
working on:  'measurements'
3072  records written to file  data_files/download_magic/measurements.txt
measurements  data put in  data_files/download_magic/measurements.txt
working on:  'criteria'
20  records written to file  data_files/download_magic/criteria.txt
criteria  data put in  data_files/download_magic/criteria.txt
working on:  'ages'
20  records written to file  data_files/download_magic/ages.txt
ages  data put in  data_files/download_magic/ages.txt
In [75]:
!eigs_s.py -f data_files/eigs_s/eigs_s_example.dat
0.33416328 0.33280227 0.33303446 -0.00016631 0.00123163 0.00135521 
0.33555713 0.33197427 0.33246869 0.00085685 0.00025266 0.00098151 
0.33585301 0.33140355 0.33274350 0.00132308 0.00117787 0.00000455 
0.33479390 0.33140817 0.33379796 -0.00043088 0.00048858 0.00045610 
0.33502916 0.33117944 0.33379149 -0.00106313 0.00029828 0.00035883 
0.33407047 0.33226910 0.33366045 -0.00000638 0.00098445 0.00005996 
0.33486328 0.33215088 0.33298591 -0.00034279 0.00038178 0.00020145 
0.33509853 0.33195898 0.33294258 0.00076976 0.00056717 0.00011960 
In [76]:
!eq_di.py -f data_files/eq_di/eq_di_example.dat > data_files/eq_di/eq_di.out
!eqarea.py -f data_files/eq_di/eq_di.out -fmt png -sav
1  saved in  eq_di_eq.png
In [77]:
Image(filename='eq_di_eq.png')
Out[77]:
In [78]:
!eqarea.py -f data_files/eqarea/fishrot.out -fmt png -sav
1  saved in  fishrot_eq.png
In [79]:
Image(filename='fishrot_eq.png')
Out[79]:

eqarea_ell.py

[notebook version]

In [80]:
!eqarea_ell.py -f data_files/eqarea_ell/tk03.out -ell B -fmt png -sav
     dec   357.8
     inc    60.3
     Edec   105.7
     Einc    10.0
     Zdec    21.0
     Zinc   -27.6
     n        20
     Zeta     4.5
     Eta     4.5
1  saved in  data_files-eqarea_ell-tk03.out_eq.png
In [81]:
Image(filename='data_files-eqarea_ell-tk03.out_eq.png')
Out[81]:

eqarea_magic.py

[notebook version]

In [82]:
!eqarea_magic.py -WD data_files/3_0/McMurdo -f sites.txt -sav -fmt "png"
-I- Using online data model
1  saved in  all_McMurdo_g_eqarea.png
In [83]:
Image(filename="all_McMurdo_g_eqarea.png")
Out[83]:
In [84]:
!download_magic.py -WD data_files/nrm_specimens_magic \
-f data_files/nrm_specimens_magic/magic_contribution_15143.txt -DM 3
working on:  'contribution'
1  records written to file  data_files/nrm_specimens_magic/contribution.txt
contribution  data put in  data_files/nrm_specimens_magic/contribution.txt
working on:  'locations'
3  records written to file  data_files/nrm_specimens_magic/locations.txt
locations  data put in  data_files/nrm_specimens_magic/locations.txt
working on:  'sites'
52  records written to file  data_files/nrm_specimens_magic/sites.txt
sites  data put in  data_files/nrm_specimens_magic/sites.txt
working on:  'samples'
437  records written to file  data_files/nrm_specimens_magic/samples.txt
samples  data put in  data_files/nrm_specimens_magic/samples.txt
working on:  'specimens'
226  records written to file  data_files/nrm_specimens_magic/specimens.txt
specimens  data put in  data_files/nrm_specimens_magic/specimens.txt
working on:  'measurements'
3072  records written to file  data_files/nrm_specimens_magic/measurements.txt
measurements  data put in  data_files/nrm_specimens_magic/measurements.txt
working on:  'criteria'
20  records written to file  data_files/nrm_specimens_magic/criteria.txt
criteria  data put in  data_files/nrm_specimens_magic/criteria.txt
working on:  'ages'
20  records written to file  data_files/nrm_specimens_magic/ages.txt
ages  data put in  data_files/nrm_specimens_magic/ages.txt
In [85]:
# plot by specimen
!eqarea_magic.py -f data_files/nrm_specimens_magic/nrm_specimens.txt -crd g -fmt png -sav -obj spc
Image('Snake_River_sr42_sr42b_sr42b1_g_eqarea.png')
-I- Using online data model
1  saved in  Snake_River_sr01_sr01e_sr01e2_g_eqarea.png
1  saved in  Snake_River_sr01_sr01g_sr01g2_g_eqarea.png
1  saved in  Snake_River_sr03_sr03f_sr03f1_g_eqarea.png
1  saved in  Snake_River_sr03_sr03h_sr03h2_g_eqarea.png
1  saved in  Snake_River_sr03_sr03k_sr03k1_g_eqarea.png
1  saved in  Snake_River_sr04_sr04e_sr04e1_g_eqarea.png
1  saved in  Snake_River_sr04_sr04f_sr04f2_g_eqarea.png
1  saved in  Snake_River_sr09_sr09b_sr09b2_g_eqarea.png
1  saved in  Snake_River_sr09_sr09e_sr09e2_g_eqarea.png
1  saved in  Snake_River_sr09_sr09f_sr09f2_g_eqarea.png
1  saved in  Snake_River_sr11_sr11a_sr11a1_g_eqarea.png
1  saved in  Snake_River_sr11_sr11b_sr11b1_g_eqarea.png
1  saved in  Snake_River_sr11_sr11c_sr11c1_g_eqarea.png
1  saved in  Snake_River_sr11_sr11e_sr11e2_g_eqarea.png
1  saved in  Snake_River_sr11_sr11g_sr11g2_g_eqarea.png
1  saved in  Snake_River_sr11_sr11i_sr11i1_g_eqarea.png
1  saved in  Snake_River_sr11_sr11j_sr11j3_g_eqarea.png
1  saved in  Snake_River_sr12_sr12c_sr12c1_g_eqarea.png
1  saved in  Snake_River_sr12_sr12h_sr12h1_g_eqarea.png
1  saved in  Snake_River_sr16_sr16e_sr16e1_g_eqarea.png
1  saved in  Snake_River_sr16_sr16g_sr16g2_g_eqarea.png
1  saved in  Snake_River_sr19_sr19a_sr19a3_g_eqarea.png
1  saved in  Snake_River_sr19_sr19b_sr19b3_g_eqarea.png
1  saved in  Snake_River_sr19_sr19h_sr19h2_g_eqarea.png
1  saved in  Snake_River_sr20_sr20d_sr20d2_g_eqarea.png
1  saved in  Snake_River_sr20_sr20e_sr20e1_g_eqarea.png
1  saved in  Snake_River_sr20_sr20i_sr20i1_g_eqarea.png
1  saved in  Snake_River_sr21_sr21d_sr21d1_g_eqarea.png
1  saved in  Snake_River_sr22_sr22b_sr22b2_g_eqarea.png
1  saved in  Snake_River_sr22_sr22d_sr22d3_g_eqarea.png
1  saved in  Snake_River_sr22_sr22e_sr22e1_g_eqarea.png
1  saved in  Snake_River_sr22_sr22f_sr22f1_g_eqarea.png
1  saved in  Snake_River_sr23_sr23a_sr23a1_g_eqarea.png
1  saved in  Snake_River_sr23_sr23b_sr23b2_g_eqarea.png
1  saved in  Snake_River_sr23_sr23d_sr23d3_g_eqarea.png
1  saved in  Snake_River_sr23_sr23g_sr23g1_g_eqarea.png
1  saved in  Snake_River_sr24_sr24a_sr24a1_g_eqarea.png
1  saved in  Snake_River_sr24_sr24b_sr24b3_g_eqarea.png
1  saved in  Snake_River_sr24_sr24c_sr24c2_g_eqarea.png
1  saved in  Snake_River_sr24_sr24d_sr24d1_g_eqarea.png
1  saved in  Snake_River_sr24_sr24j_sr24j2_g_eqarea.png
1  saved in  Snake_River_sr25_sr25b_sr25b2_g_eqarea.png
1  saved in  Snake_River_sr25_sr25d_sr25d2_g_eqarea.png
1  saved in  Snake_River_sr25_sr25e_sr25e2_g_eqarea.png
1  saved in  Snake_River_sr25_sr25f_sr25f3_g_eqarea.png
1  saved in  Snake_River_sr25_sr25h_sr25h1_g_eqarea.png
1  saved in  Snake_River_sr26_sr26a_sr26a3_g_eqarea.png
1  saved in  Snake_River_sr26_sr26c_sr26c3_g_eqarea.png
1  saved in  Snake_River_sr26_sr26e_sr26e3_g_eqarea.png
1  saved in  Snake_River_sr26_sr26f_sr26f1_g_eqarea.png
1  saved in  Snake_River_sr26_sr26i_sr26i1_g_eqarea.png
1  saved in  Snake_River_sr27_sr27a_sr27a2_g_eqarea.png
1  saved in  Snake_River_sr27_sr27c_sr27c1_g_eqarea.png
1  saved in  Snake_River_sr27_sr27e_sr27e2_g_eqarea.png
1  saved in  Snake_River_sr28_sr28a_sr28a1_g_eqarea.png
1  saved in  Snake_River_sr28_sr28g_sr28g2_g_eqarea.png
1  saved in  Snake_River_sr29_sr29g_sr29g2_g_eqarea.png
1  saved in  Snake_River_sr30_sr30b_sr30b2_g_eqarea.png
1  saved in  Snake_River_sr31_sr31h_sr31h2_g_eqarea.png
1  saved in  Snake_River_sr34_sr34f_sr34f2_g_eqarea.png
1  saved in  Snake_River_sr34_sr34i_sr34i3_g_eqarea.png
1  saved in  Snake_River_sr36_sr36a_sr36a2_g_eqarea.png
1  saved in  Snake_River_sr36_sr36b_sr36b1_g_eqarea.png
1  saved in  Snake_River_sr36_sr36c_sr36c1_g_eqarea.png
1  saved in  Snake_River_sr36_sr36d_sr36d1_g_eqarea.png
1  saved in  Snake_River_sr36_sr36e_sr36e1_g_eqarea.png
1  saved in  Snake_River_sr36_sr36i_sr36i2_g_eqarea.png
1  saved in  Snake_River_sr37_sr37g_sr37g2_g_eqarea.png
1  saved in  Snake_River_sr37_sr37j_sr37j2_g_eqarea.png
1  saved in  Snake_River_sr39_sr39g_sr39g3_g_eqarea.png
1  saved in  Snake_River_sr39_sr39h_sr39h3_g_eqarea.png
1  saved in  Snake_River_sr40_sr40f_sr40f3_g_eqarea.png
1  saved in  Snake_River_sr42_sr42c_sr42c3_g_eqarea.png
1  saved in  Snake_River_sr42_sr42f_sr42f2_g_eqarea.png
1  saved in  Snake_River_sr42_sr42h_sr42h2_g_eqarea.png
1  saved in  Snake_River_sr42_sr42j_sr42j2_g_eqarea.png
1  saved in  Snake_River_sr01_sr01a_sr01a1_g_eqarea.png
1  saved in  Snake_River_sr01_sr01a_sr01a2_g_eqarea.png
1  saved in  Snake_River_sr01_sr01c_sr01c2_g_eqarea.png
1  saved in  Snake_River_sr01_sr01d_sr01d1_g_eqarea.png
1  saved in  Snake_River_sr01_sr01i_sr01i1_g_eqarea.png
1  saved in  Snake_River_sr03_sr03a_sr03a1_g_eqarea.png
1  saved in  Snake_River_sr03_sr03b_sr03b1_g_eqarea.png
1  saved in  Snake_River_sr03_sr03c_sr03c1_g_eqarea.png
1  saved in  Snake_River_sr03_sr03e_sr03e1_g_eqarea.png
1  saved in  Snake_River_sr09_sr09f_sr09f1_g_eqarea.png
1  saved in  Snake_River_sr21_sr21h_sr21h1_g_eqarea.png
1  saved in  Snake_River_sr28_sr28b_sr28b1_g_eqarea.png
1  saved in  Snake_River_sr28_sr28c_sr28c1_g_eqarea.png
1  saved in  Snake_River_sr28_sr28e_sr28e1_g_eqarea.png
1  saved in  Snake_River_sr28_sr28f_sr28f1_g_eqarea.png
1  saved in  Snake_River_sr28_sr28h_sr28h1_g_eqarea.png
1  saved in  Snake_River_sr29_sr29a_sr29a1_g_eqarea.png
1  saved in  Snake_River_sr29_sr29a_sr29a2_g_eqarea.png
1  saved in  Snake_River_sr29_sr29b_sr29b1_g_eqarea.png
1  saved in  Snake_River_sr29_sr29c_sr29c1_g_eqarea.png
1  saved in  Snake_River_sr29_sr29g_sr29g1_g_eqarea.png
1  saved in  Snake_River_sr29_sr29h_sr29h1_g_eqarea.png
1  saved in  Snake_River_sr30_sr30a_sr30a1_g_eqarea.png
1  saved in  Snake_River_sr30_sr30a_sr30a2_g_eqarea.png
1  saved in  Snake_River_sr30_sr30c_sr30c1_g_eqarea.png
1  saved in  Snake_River_sr30_sr30e_sr30e1_g_eqarea.png
1  saved in  Snake_River_sr30_sr30i_sr30i1_g_eqarea.png
1  saved in  Snake_River_sr31_sr31a_sr31a1_g_eqarea.png
1  saved in  Snake_River_sr31_sr31a_sr31a2_g_eqarea.png
1  saved in  Snake_River_sr31_sr31b_sr31b3_g_eqarea.png
1  saved in  Snake_River_sr31_sr31c_sr31c1_g_eqarea.png
1  saved in  Snake_River_sr31_sr31d_sr31d1_g_eqarea.png
1  saved in  Snake_River_sr31_sr31f_sr31f1_g_eqarea.png
1  saved in  Snake_River_sr34_sr34b_sr34b1_g_eqarea.png
1  saved in  Snake_River_sr34_sr34c_sr34c1_g_eqarea.png
1  saved in  Snake_River_sr34_sr34f_sr34f3_g_eqarea.png
1  saved in  Snake_River_sr34_sr34j_sr34j1_g_eqarea.png
1  saved in  Snake_River_sr34_sr34k_sr34k1_g_eqarea.png
1  saved in  Snake_River_sr37_sr37a_sr37a2_g_eqarea.png
1  saved in  Snake_River_sr37_sr37b_sr37b1_g_eqarea.png
1  saved in  Snake_River_sr37_sr37e_sr37e1_g_eqarea.png
1  saved in  Snake_River_sr37_sr37h_sr37h1_g_eqarea.png
1  saved in  Snake_River_sr37_sr37j_sr37j1_g_eqarea.png
1  saved in  Snake_River_sr39_sr39a_sr39a1_g_eqarea.png
1  saved in  Snake_River_sr39_sr39b_sr39b1_g_eqarea.png
1  saved in  Snake_River_sr39_sr39c_sr39c1_g_eqarea.png
1  saved in  Snake_River_sr39_sr39i_sr39i1_g_eqarea.png
1  saved in  Snake_River_sr40_sr40a_sr40a1_g_eqarea.png
1  saved in  Snake_River_sr40_sr40c_sr40c2_g_eqarea.png
1  saved in  Snake_River_sr40_sr40d_sr40d1_g_eqarea.png
1  saved in  Snake_River_sr40_sr40g_sr40g1_g_eqarea.png
1  saved in  Snake_River_sr01_sr01f_sr01f2_g_eqarea.png
1  saved in  Snake_River_sr03_sr03g_sr03g1_g_eqarea.png
1  saved in  Snake_River_sr04_sr04d_sr04d2_g_eqarea.png
1  saved in  Snake_River_sr04_sr04g_sr04g1_g_eqarea.png
1  saved in  Snake_River_sr04_sr04h_sr04h3_g_eqarea.png
1  saved in  Snake_River_sr09_sr09c_sr09c3_g_eqarea.png
1  saved in  Snake_River_sr09_sr09g_sr09g1_g_eqarea.png
1  saved in  Snake_River_sr09_sr09i_sr09i1_g_eqarea.png
1  saved in  Snake_River_sr11_sr11f_sr11f1_g_eqarea.png
1  saved in  Snake_River_sr12_sr12a_sr12a3_g_eqarea.png
1  saved in  Snake_River_sr12_sr12b_sr12b1_g_eqarea.png
1  saved in  Snake_River_sr12_sr12e_sr12e1_g_eqarea.png
1  saved in  Snake_River_sr16_sr16a_sr16a1_g_eqarea.png
1  saved in  Snake_River_sr16_sr16b_sr16b1_g_eqarea.png
1  saved in  Snake_River_sr16_sr16c_sr16c1_g_eqarea.png
1  saved in  Snake_River_sr16_sr16d_sr16d1_g_eqarea.png
1  saved in  Snake_River_sr16_sr16f_sr16f1_g_eqarea.png
1  saved in  Snake_River_sr19_sr19e_sr19e2_g_eqarea.png
1  saved in  Snake_River_sr19_sr19i_sr19i1_g_eqarea.png
1  saved in  Snake_River_sr20_sr20c_sr20c1_g_eqarea.png
1  saved in  Snake_River_sr20_sr20f_sr20f1_g_eqarea.png
1  saved in  Snake_River_sr20_sr20g_sr20g1_g_eqarea.png
1  saved in  Snake_River_sr20_sr20i_sr20i2_g_eqarea.png
1  saved in  Snake_River_sr20_sr20j_sr20j2_g_eqarea.png
1  saved in  Snake_River_sr21_sr21b_sr21b2_g_eqarea.png
1  saved in  Snake_River_sr21_sr21g_sr21g2_g_eqarea.png
1  saved in  Snake_River_sr21_sr21j_sr21j2_g_eqarea.png
1  saved in  Snake_River_sr22_sr22a_sr22a1_g_eqarea.png
1  saved in  Snake_River_sr22_sr22g_sr22g1_g_eqarea.png
1  saved in  Snake_River_sr22_sr22i_sr22i2_g_eqarea.png
1  saved in  Snake_River_sr23_sr23c_sr23c2_g_eqarea.png
1  saved in  Snake_River_sr23_sr23e_sr23e1_g_eqarea.png
1  saved in  Snake_River_sr23_sr23f_sr23f1_g_eqarea.png
1  saved in  Snake_River_sr24_sr24i_sr24i2_g_eqarea.png
1  saved in  Snake_River_sr25_sr25c_sr25c2_g_eqarea.png
1  saved in  Snake_River_sr26_sr26b_sr26b2_g_eqarea.png
1  saved in  Snake_River_sr26_sr26e_sr26e2_g_eqarea.png
1  saved in  Snake_River_sr26_sr26g_sr26g1_g_eqarea.png
1  saved in  Snake_River_sr27_sr27c_sr27c2_g_eqarea.png
1  saved in  Snake_River_sr27_sr27d_sr27d1_g_eqarea.png
1  saved in  Snake_River_sr28_sr28c_sr28c2_g_eqarea.png
1  saved in  Snake_River_sr29_sr29e_sr29e3_g_eqarea.png
1  saved in  Snake_River_sr30_sr30d_sr30d2_g_eqarea.png
1  saved in  Snake_River_sr31_sr31b_sr31b1_g_eqarea.png
1  saved in  Snake_River_sr34_sr34a_sr34a1_g_eqarea.png
1  saved in  Snake_River_sr36_sr36d_sr36d2_g_eqarea.png
1  saved in  Snake_River_sr37_sr37i_sr37i2_g_eqarea.png
1  saved in  Snake_River_sr39_sr39j_sr39j2_g_eqarea.png
1  saved in  Snake_River_sr40_sr40e_sr40e1_g_eqarea.png
1  saved in  Snake_River_sr42_sr42b_sr42b1_g_eqarea.png
Out[85]:
In [86]:
# plotting all with no sites file

# get rid of any png files lying around
for fname in glob.glob("*.png"):
    os.remove(fname)

# temporarily hide sites file
try:
    os.rename('data_files/nrm_specimens_magic/sites.txt', 'data_files/nrm_specimens_magic/temp.txt')
except FileNotFoundError:
    pass
    
# run eqarea_magic    
!eqarea_magic.py -f data_files/nrm_specimens_magic/nrm_specimens.txt -crd g -fmt png -sav -obj all
Image('all_g_eqarea.png')
-I- Using online data model
-W- Couldn't read in sites data
-I- Make sure you've provided the correct file name
-W- Couldn't read in sites data
-I- Make sure you've provided the correct file name
-W- Couldn't read in sites data
-I- Make sure you've provided the correct file name
1  saved in  all_g_eqarea.png
Out[86]:
In [87]:
# plotting by sample with no sites file
# get rid of any png files lying around
for fname in glob.glob("*.png"):
    os.remove(fname)
!eqarea_magic.py -f data_files/nrm_specimens_magic/nrm_specimens.txt -crd g -fmt png -sav -obj sam
Image('sr42_sr42b_g_eqarea.png')
-I- Using online data model
-W- Couldn't read in sites data
-I- Make sure you've provided the correct file name
-W- Couldn't read in sites data
-I- Make sure you've provided the correct file name
-W- Couldn't read in sites data
-I- Make sure you've provided the correct file name
1  saved in  sr01_sr01e_g_eqarea.png
1  saved in  sr01_sr01g_g_eqarea.png
1  saved in  sr03_sr03f_g_eqarea.png
1  saved in  sr03_sr03h_g_eqarea.png
1  saved in  sr03_sr03k_g_eqarea.png
1  saved in  sr04_sr04e_g_eqarea.png
1  saved in  sr04_sr04f_g_eqarea.png
1  saved in  sr09_sr09b_g_eqarea.png
1  saved in  sr09_sr09e_g_eqarea.png
1  saved in  sr09_sr09f_g_eqarea.png
1  saved in  sr11_sr11a_g_eqarea.png
1  saved in  sr11_sr11b_g_eqarea.png
1  saved in  sr11_sr11c_g_eqarea.png
1  saved in  sr11_sr11e_g_eqarea.png
1  saved in  sr11_sr11g_g_eqarea.png
1  saved in  sr11_sr11i_g_eqarea.png
1  saved in  sr11_sr11j_g_eqarea.png
1  saved in  sr12_sr12c_g_eqarea.png
1  saved in  sr12_sr12h_g_eqarea.png
1  saved in  sr16_sr16e_g_eqarea.png
1  saved in  sr16_sr16g_g_eqarea.png
1  saved in  sr19_sr19a_g_eqarea.png
1  saved in  sr19_sr19b_g_eqarea.png
1  saved in  sr19_sr19h_g_eqarea.png
1  saved in  sr20_sr20d_g_eqarea.png
1  saved in  sr20_sr20e_g_eqarea.png
1  saved in  sr20_sr20i_g_eqarea.png
1  saved in  sr21_sr21d_g_eqarea.png
1  saved in  sr22_sr22b_g_eqarea.png
1  saved in  sr22_sr22d_g_eqarea.png
1  saved in  sr22_sr22e_g_eqarea.png
1  saved in  sr22_sr22f_g_eqarea.png
1  saved in  sr23_sr23a_g_eqarea.png
1  saved in  sr23_sr23b_g_eqarea.png
1  saved in  sr23_sr23d_g_eqarea.png
1  saved in  sr23_sr23g_g_eqarea.png
1  saved in  sr24_sr24a_g_eqarea.png
1  saved in  sr24_sr24b_g_eqarea.png
1  saved in  sr24_sr24c_g_eqarea.png
1  saved in  sr24_sr24d_g_eqarea.png
1  saved in  sr24_sr24j_g_eqarea.png
1  saved in  sr25_sr25b_g_eqarea.png
1  saved in  sr25_sr25d_g_eqarea.png
1  saved in  sr25_sr25e_g_eqarea.png
1  saved in  sr25_sr25f_g_eqarea.png
1  saved in  sr25_sr25h_g_eqarea.png
1  saved in  sr26_sr26a_g_eqarea.png
1  saved in  sr26_sr26c_g_eqarea.png
1  saved in  sr26_sr26e_g_eqarea.png
1  saved in  sr26_sr26f_g_eqarea.png
1  saved in  sr26_sr26i_g_eqarea.png
1  saved in  sr27_sr27a_g_eqarea.png
1  saved in  sr27_sr27c_g_eqarea.png
1  saved in  sr27_sr27e_g_eqarea.png
1  saved in  sr28_sr28a_g_eqarea.png
1  saved in  sr28_sr28g_g_eqarea.png
1  saved in  sr29_sr29g_g_eqarea.png
1  saved in  sr30_sr30b_g_eqarea.png
1  saved in  sr31_sr31h_g_eqarea.png
1  saved in  sr34_sr34f_g_eqarea.png
1  saved in  sr34_sr34i_g_eqarea.png
1  saved in  sr36_sr36a_g_eqarea.png
1  saved in  sr36_sr36b_g_eqarea.png
1  saved in  sr36_sr36c_g_eqarea.png
1  saved in  sr36_sr36d_g_eqarea.png
1  saved in  sr36_sr36e_g_eqarea.png
1  saved in  sr36_sr36i_g_eqarea.png
1  saved in  sr37_sr37g_g_eqarea.png
1  saved in  sr37_sr37j_g_eqarea.png
1  saved in  sr39_sr39g_g_eqarea.png
1  saved in  sr39_sr39h_g_eqarea.png
1  saved in  sr40_sr40f_g_eqarea.png
1  saved in  sr42_sr42c_g_eqarea.png
1  saved in  sr42_sr42f_g_eqarea.png
1  saved in  sr42_sr42h_g_eqarea.png
1  saved in  sr42_sr42j_g_eqarea.png
1  saved in  sr01_sr01a_g_eqarea.png
1  saved in  sr01_sr01c_g_eqarea.png
1  saved in  sr01_sr01d_g_eqarea.png
1  saved in  sr01_sr01i_g_eqarea.png
1  saved in  sr03_sr03a_g_eqarea.png
1  saved in  sr03_sr03b_g_eqarea.png
1  saved in  sr03_sr03c_g_eqarea.png
1  saved in  sr03_sr03e_g_eqarea.png
1  saved in  sr21_sr21h_g_eqarea.png
1  saved in  sr28_sr28b_g_eqarea.png
1  saved in  sr28_sr28c_g_eqarea.png
1  saved in  sr28_sr28e_g_eqarea.png
1  saved in  sr28_sr28f_g_eqarea.png
1  saved in  sr28_sr28h_g_eqarea.png
1  saved in  sr29_sr29a_g_eqarea.png
1  saved in  sr29_sr29b_g_eqarea.png
1  saved in  sr29_sr29c_g_eqarea.png
1  saved in  sr29_sr29h_g_eqarea.png
1  saved in  sr30_sr30a_g_eqarea.png
1  saved in  sr30_sr30c_g_eqarea.png
1  saved in  sr30_sr30e_g_eqarea.png
1  saved in  sr30_sr30i_g_eqarea.png
1  saved in  sr31_sr31a_g_eqarea.png
1  saved in  sr31_sr31b_g_eqarea.png
1  saved in  sr31_sr31c_g_eqarea.png
1  saved in  sr31_sr31d_g_eqarea.png
1  saved in  sr31_sr31f_g_eqarea.png
1  saved in  sr34_sr34b_g_eqarea.png
1  saved in  sr34_sr34c_g_eqarea.png
1  saved in  sr34_sr34j_g_eqarea.png
1  saved in  sr34_sr34k_g_eqarea.png
1  saved in  sr37_sr37a_g_eqarea.png
1  saved in  sr37_sr37b_g_eqarea.png
1  saved in  sr37_sr37e_g_eqarea.png
1  saved in  sr37_sr37h_g_eqarea.png
1  saved in  sr39_sr39a_g_eqarea.png
1  saved in  sr39_sr39b_g_eqarea.png
1  saved in  sr39_sr39c_g_eqarea.png
1  saved in  sr39_sr39i_g_eqarea.png
1  saved in  sr40_sr40a_g_eqarea.png
1  saved in  sr40_sr40c_g_eqarea.png
1  saved in  sr40_sr40d_g_eqarea.png
1  saved in  sr40_sr40g_g_eqarea.png
1  saved in  sr01_sr01f_g_eqarea.png
1  saved in  sr03_sr03g_g_eqarea.png
1  saved in  sr04_sr04d_g_eqarea.png
1  saved in  sr04_sr04g_g_eqarea.png
1  saved in  sr04_sr04h_g_eqarea.png
1  saved in  sr09_sr09c_g_eqarea.png
1  saved in  sr09_sr09g_g_eqarea.png
1  saved in  sr09_sr09i_g_eqarea.png
1  saved in  sr11_sr11f_g_eqarea.png
1  saved in  sr12_sr12a_g_eqarea.png
1  saved in  sr12_sr12b_g_eqarea.png
1  saved in  sr12_sr12e_g_eqarea.png
1  saved in  sr16_sr16a_g_eqarea.png
1  saved in  sr16_sr16b_g_eqarea.png
1  saved in  sr16_sr16c_g_eqarea.png
1  saved in  sr16_sr16d_g_eqarea.png
1  saved in  sr16_sr16f_g_eqarea.png
1  saved in  sr19_sr19e_g_eqarea.png
1  saved in  sr19_sr19i_g_eqarea.png
1  saved in  sr20_sr20c_g_eqarea.png
1  saved in  sr20_sr20f_g_eqarea.png
1  saved in  sr20_sr20g_g_eqarea.png
1  saved in  sr20_sr20j_g_eqarea.png
1  saved in  sr21_sr21b_g_eqarea.png
1  saved in  sr21_sr21g_g_eqarea.png
1  saved in  sr21_sr21j_g_eqarea.png
1  saved in  sr22_sr22a_g_eqarea.png
1  saved in  sr22_sr22g_g_eqarea.png
1  saved in  sr22_sr22i_g_eqarea.png
1  saved in  sr23_sr23c_g_eqarea.png
1  saved in  sr23_sr23e_g_eqarea.png
1  saved in  sr23_sr23f_g_eqarea.png
1  saved in  sr24_sr24i_g_eqarea.png
1  saved in  sr25_sr25c_g_eqarea.png
1  saved in  sr26_sr26b_g_eqarea.png
1  saved in  sr26_sr26g_g_eqarea.png
1  saved in  sr27_sr27d_g_eqarea.png
1  saved in  sr29_sr29e_g_eqarea.png
1  saved in  sr30_sr30d_g_eqarea.png
1  saved in  sr34_sr34a_g_eqarea.png
1  saved in  sr37_sr37i_g_eqarea.png
1  saved in  sr39_sr39j_g_eqarea.png
1  saved in  sr40_sr40e_g_eqarea.png
1  saved in  sr42_sr42b_g_eqarea.png
Out[87]:
In [88]:
# can't get site data with no site or sample file, will fail gracefully
!mv data_files/nrm_specimens_magic/samples.txt data_files/nrm_specimens_magic/temp_samples.txt
!eqarea_magic.py -f data_files/nrm_specimens_magic/nrm_specimens.txt -crd g -fmt png -sav -obj sit
!mv  data_files/nrm_specimens_magic/temp_samples.txt data_files/nrm_specimens_magic/samples.txt
-I- Using online data model
-W- Couldn't read in samples data
-I- Make sure you've provided the correct file name
-W- Couldn't read in samples data
-I- Make sure you've provided the correct file name
-W- Couldn't read in samples data
-I- Make sure you've provided the correct file name
-W- Couldn't read in samples data
-I- Make sure you've provided the correct file name
-E- You can't plot by site with the data provided
In [89]:
# plotting by sample
# get rid of any png files lying around
for fname in glob.glob("*.png"):
    os.remove(fname)
try:
    os.rename('data_files/nrm_specimens_magic/temp.txt', 'data_files/nrm_specimens_magic/sites.txt')
except FileNotFoundError:
    pass
!eqarea_magic.py -f data_files/nrm_specimens_magic/nrm_specimens.txt -crd g -fmt png -sav -obj sam
Image('Snake_River_sr42_sr42b_g_eqarea.png')
-I- Using online data model
1  saved in  Snake_River_sr01_sr01e_g_eqarea.png
1  saved in  Snake_River_sr01_sr01g_g_eqarea.png
1  saved in  Snake_River_sr03_sr03f_g_eqarea.png
1  saved in  Snake_River_sr03_sr03h_g_eqarea.png
1  saved in  Snake_River_sr03_sr03k_g_eqarea.png
1  saved in  Snake_River_sr04_sr04e_g_eqarea.png
1  saved in  Snake_River_sr04_sr04f_g_eqarea.png
1  saved in  Snake_River_sr09_sr09b_g_eqarea.png
1  saved in  Snake_River_sr09_sr09e_g_eqarea.png
1  saved in  Snake_River_sr09_sr09f_g_eqarea.png
1  saved in  Snake_River_sr11_sr11a_g_eqarea.png
1  saved in  Snake_River_sr11_sr11b_g_eqarea.png
1  saved in  Snake_River_sr11_sr11c_g_eqarea.png
1  saved in  Snake_River_sr11_sr11e_g_eqarea.png
1  saved in  Snake_River_sr11_sr11g_g_eqarea.png
1  saved in  Snake_River_sr11_sr11i_g_eqarea.png
1  saved in  Snake_River_sr11_sr11j_g_eqarea.png
1  saved in  Snake_River_sr12_sr12c_g_eqarea.png
1  saved in  Snake_River_sr12_sr12h_g_eqarea.png
1  saved in  Snake_River_sr16_sr16e_g_eqarea.png
1  saved in  Snake_River_sr16_sr16g_g_eqarea.png
1  saved in  Snake_River_sr19_sr19a_g_eqarea.png
1  saved in  Snake_River_sr19_sr19b_g_eqarea.png
1  saved in  Snake_River_sr19_sr19h_g_eqarea.png
1  saved in  Snake_River_sr20_sr20d_g_eqarea.png
1  saved in  Snake_River_sr20_sr20e_g_eqarea.png
1  saved in  Snake_River_sr20_sr20i_g_eqarea.png
1  saved in  Snake_River_sr21_sr21d_g_eqarea.png
1  saved in  Snake_River_sr22_sr22b_g_eqarea.png
1  saved in  Snake_River_sr22_sr22d_g_eqarea.png
1  saved in  Snake_River_sr22_sr22e_g_eqarea.png
1  saved in  Snake_River_sr22_sr22f_g_eqarea.png
1  saved in  Snake_River_sr23_sr23a_g_eqarea.png
1  saved in  Snake_River_sr23_sr23b_g_eqarea.png
1  saved in  Snake_River_sr23_sr23d_g_eqarea.png
1  saved in  Snake_River_sr23_sr23g_g_eqarea.png
1  saved in  Snake_River_sr24_sr24a_g_eqarea.png
1  saved in  Snake_River_sr24_sr24b_g_eqarea.png
1  saved in  Snake_River_sr24_sr24c_g_eqarea.png
1  saved in  Snake_River_sr24_sr24d_g_eqarea.png
1  saved in  Snake_River_sr24_sr24j_g_eqarea.png
1  saved in  Snake_River_sr25_sr25b_g_eqarea.png
1  saved in  Snake_River_sr25_sr25d_g_eqarea.png
1  saved in  Snake_River_sr25_sr25e_g_eqarea.png
1  saved in  Snake_River_sr25_sr25f_g_eqarea.png
1  saved in  Snake_River_sr25_sr25h_g_eqarea.png
1  saved in  Snake_River_sr26_sr26a_g_eqarea.png
1  saved in  Snake_River_sr26_sr26c_g_eqarea.png
1  saved in  Snake_River_sr26_sr26e_g_eqarea.png
1  saved in  Snake_River_sr26_sr26f_g_eqarea.png
1  saved in  Snake_River_sr26_sr26i_g_eqarea.png
1  saved in  Snake_River_sr27_sr27a_g_eqarea.png
1  saved in  Snake_River_sr27_sr27c_g_eqarea.png
1  saved in  Snake_River_sr27_sr27e_g_eqarea.png
1  saved in  Snake_River_sr28_sr28a_g_eqarea.png
1  saved in  Snake_River_sr28_sr28g_g_eqarea.png
1  saved in  Snake_River_sr29_sr29g_g_eqarea.png
1  saved in  Snake_River_sr30_sr30b_g_eqarea.png
1  saved in  Snake_River_sr31_sr31h_g_eqarea.png
1  saved in  Snake_River_sr34_sr34f_g_eqarea.png
1  saved in  Snake_River_sr34_sr34i_g_eqarea.png
1  saved in  Snake_River_sr36_sr36a_g_eqarea.png
1  saved in  Snake_River_sr36_sr36b_g_eqarea.png
1  saved in  Snake_River_sr36_sr36c_g_eqarea.png
1  saved in  Snake_River_sr36_sr36d_g_eqarea.png
1  saved in  Snake_River_sr36_sr36e_g_eqarea.png
1  saved in  Snake_River_sr36_sr36i_g_eqarea.png
1  saved in  Snake_River_sr37_sr37g_g_eqarea.png
1  saved in  Snake_River_sr37_sr37j_g_eqarea.png
1  saved in  Snake_River_sr39_sr39g_g_eqarea.png
1  saved in  Snake_River_sr39_sr39h_g_eqarea.png
1  saved in  Snake_River_sr40_sr40f_g_eqarea.png
1  saved in  Snake_River_sr42_sr42c_g_eqarea.png
1  saved in  Snake_River_sr42_sr42f_g_eqarea.png
1  saved in  Snake_River_sr42_sr42h_g_eqarea.png
1  saved in  Snake_River_sr42_sr42j_g_eqarea.png
1  saved in  Snake_River_sr01_sr01a_g_eqarea.png
1  saved in  Snake_River_sr01_sr01c_g_eqarea.png
1  saved in  Snake_River_sr01_sr01d_g_eqarea.png
1  saved in  Snake_River_sr01_sr01i_g_eqarea.png
1  saved in  Snake_River_sr03_sr03a_g_eqarea.png
1  saved in  Snake_River_sr03_sr03b_g_eqarea.png
1  saved in  Snake_River_sr03_sr03c_g_eqarea.png
1  saved in  Snake_River_sr03_sr03e_g_eqarea.png
1  saved in  Snake_River_sr21_sr21h_g_eqarea.png
1  saved in  Snake_River_sr28_sr28b_g_eqarea.png
1  saved in  Snake_River_sr28_sr28c_g_eqarea.png
1  saved in  Snake_River_sr28_sr28e_g_eqarea.png
1  saved in  Snake_River_sr28_sr28f_g_eqarea.png
1  saved in  Snake_River_sr28_sr28h_g_eqarea.png
1  saved in  Snake_River_sr29_sr29a_g_eqarea.png
1  saved in  Snake_River_sr29_sr29b_g_eqarea.png
1  saved in  Snake_River_sr29_sr29c_g_eqarea.png
1  saved in  Snake_River_sr29_sr29h_g_eqarea.png
1  saved in  Snake_River_sr30_sr30a_g_eqarea.png
1  saved in  Snake_River_sr30_sr30c_g_eqarea.png
1  saved in  Snake_River_sr30_sr30e_g_eqarea.png
1  saved in  Snake_River_sr30_sr30i_g_eqarea.png
1  saved in  Snake_River_sr31_sr31a_g_eqarea.png
1  saved in  Snake_River_sr31_sr31b_g_eqarea.png
1  saved in  Snake_River_sr31_sr31c_g_eqarea.png
1  saved in  Snake_River_sr31_sr31d_g_eqarea.png
1  saved in  Snake_River_sr31_sr31f_g_eqarea.png
1  saved in  Snake_River_sr34_sr34b_g_eqarea.png
1  saved in  Snake_River_sr34_sr34c_g_eqarea.png
1  saved in  Snake_River_sr34_sr34j_g_eqarea.png
1  saved in  Snake_River_sr34_sr34k_g_eqarea.png
1  saved in  Snake_River_sr37_sr37a_g_eqarea.png
1  saved in  Snake_River_sr37_sr37b_g_eqarea.png
1  saved in  Snake_River_sr37_sr37e_g_eqarea.png
1  saved in  Snake_River_sr37_sr37h_g_eqarea.png
1  saved in  Snake_River_sr39_sr39a_g_eqarea.png
1  saved in  Snake_River_sr39_sr39b_g_eqarea.png
1  saved in  Snake_River_sr39_sr39c_g_eqarea.png
1  saved in  Snake_River_sr39_sr39i_g_eqarea.png
1  saved in  Snake_River_sr40_sr40a_g_eqarea.png
1  saved in  Snake_River_sr40_sr40c_g_eqarea.png
1  saved in  Snake_River_sr40_sr40d_g_eqarea.png
1  saved in  Snake_River_sr40_sr40g_g_eqarea.png
1  saved in  Snake_River_sr01_sr01f_g_eqarea.png
1  saved in  Snake_River_sr03_sr03g_g_eqarea.png
1  saved in  Snake_River_sr04_sr04d_g_eqarea.png
1  saved in  Snake_River_sr04_sr04g_g_eqarea.png
1  saved in  Snake_River_sr04_sr04h_g_eqarea.png
1  saved in  Snake_River_sr09_sr09c_g_eqarea.png
1  saved in  Snake_River_sr09_sr09g_g_eqarea.png
1  saved in  Snake_River_sr09_sr09i_g_eqarea.png
1  saved in  Snake_River_sr11_sr11f_g_eqarea.png
1  saved in  Snake_River_sr12_sr12a_g_eqarea.png
1  saved in  Snake_River_sr12_sr12b_g_eqarea.png
1  saved in  Snake_River_sr12_sr12e_g_eqarea.png
1  saved in  Snake_River_sr16_sr16a_g_eqarea.png
1  saved in  Snake_River_sr16_sr16b_g_eqarea.png
1  saved in  Snake_River_sr16_sr16c_g_eqarea.png
1  saved in  Snake_River_sr16_sr16d_g_eqarea.png
1  saved in  Snake_River_sr16_sr16f_g_eqarea.png
1  saved in  Snake_River_sr19_sr19e_g_eqarea.png
1  saved in  Snake_River_sr19_sr19i_g_eqarea.png
1  saved in  Snake_River_sr20_sr20c_g_eqarea.png
1  saved in  Snake_River_sr20_sr20f_g_eqarea.png
1  saved in  Snake_River_sr20_sr20g_g_eqarea.png
1  saved in  Snake_River_sr20_sr20j_g_eqarea.png
1  saved in  Snake_River_sr21_sr21b_g_eqarea.png
1  saved in  Snake_River_sr21_sr21g_g_eqarea.png
1  saved in  Snake_River_sr21_sr21j_g_eqarea.png
1  saved in  Snake_River_sr22_sr22a_g_eqarea.png
1  saved in  Snake_River_sr22_sr22g_g_eqarea.png
1  saved in  Snake_River_sr22_sr22i_g_eqarea.png
1  saved in  Snake_River_sr23_sr23c_g_eqarea.png
1  saved in  Snake_River_sr23_sr23e_g_eqarea.png
1  saved in  Snake_River_sr23_sr23f_g_eqarea.png
1  saved in  Snake_River_sr24_sr24i_g_eqarea.png
1  saved in  Snake_River_sr25_sr25c_g_eqarea.png
1  saved in  Snake_River_sr26_sr26b_g_eqarea.png
1  saved in  Snake_River_sr26_sr26g_g_eqarea.png
1  saved in  Snake_River_sr27_sr27d_g_eqarea.png
1  saved in  Snake_River_sr29_sr29e_g_eqarea.png
1  saved in  Snake_River_sr30_sr30d_g_eqarea.png
1  saved in  Snake_River_sr34_sr34a_g_eqarea.png
1  saved in  Snake_River_sr37_sr37i_g_eqarea.png
1  saved in  Snake_River_sr39_sr39j_g_eqarea.png
1  saved in  Snake_River_sr40_sr40e_g_eqarea.png
1  saved in  Snake_River_sr42_sr42b_g_eqarea.png
Out[89]:
In [90]:
# plotting all
for fname in glob.glob("*.png"):
    os.remove(fname)
!eqarea_magic.py -WD data_files/nrm_specimens_magic/ -f nrm_specimens.txt -crd g -fmt png -sav -obj all
Image('all_Snake_River_g_eqarea.png')
-I- Using online data model
1  saved in  all_Snake_River_g_eqarea.png
Out[90]:
In [91]:
# using unknown option for -obj, will default to plotting all instead
for fname in glob.glob("*.png"):
    os.remove(fname)
!eqarea_magic.py -f data_files/nrm_specimens_magic/samples.txt -crd g -fmt png -sav -obj loc  # will use 'all'
Image('all_Snake_River_g_eqarea.png')
-I- Using online data model
1  saved in  all_Snake_River_g_eqarea.png
Out[91]:

eqarea_magic2.py

In [92]:
!eqarea_magic2.py -obj loc -crd g -f data_files/eqarea_magic/pmag_results.txt\
    -ell Be -fmt png -sav
1  saved in  Snake_River_gu_eqarea.png
In [93]:
Image(filename='Snake_River_gu_eqarea.png')
Out[93]:
In [94]:
!find_ei.py -f data_files/find_EI/find_EI_example.dat -fmt png -sav -n 300
Bootstrapping.... be patient
25  out of  300
50  out of  300
75  out of  300
100  out of  300
125  out of  300
150  out of  300
175  out of  300
200  out of  300
225  out of  300
250  out of  300
275  out of  300
300  out of  300
1  saved in  findEI_eq.png
2  saved in  findEI_ei.png
3  saved in  findEI_cdf.png
4  saved in  findEI_v2.png
In [95]:
Image(filename='findEI_ei.png')
Out[95]:
In [96]:
Image(filename='findEI_cdf.png')
Out[96]:
In [97]:
Image(filename='findEI_eq.png')
Out[97]:
In [98]:
Image(filename='findEI_v2.png')
Out[98]:
In [99]:
!fisher.py -k 30 -n 10
  230.4    82.5 
  179.5    74.6 
  215.6    85.6 
   85.7    79.3 
   35.5    84.9 
  333.6    87.3 
  316.4    70.5 
  173.4    80.9 
  108.9    84.8 
   57.5    83.5 
In [100]:
!fishqq.py -f data_files/fishqq/fishqq_example.txt -fmt png -sav
1  saved in  data_files-fishqq-fishqq_example.txt_unf1.png
2  saved in  data_files-fishqq-fishqq_example.txt_exp1.png
In [101]:
Image(filename='data_files-fishqq-fishqq_example.txt_unf1.png')
Out[101]:
In [102]:
Image(filename='data_files-fishqq-fishqq_example.txt_exp1.png')
Out[102]:
In [103]:
!fishrot.py -n 5 -D 33 -I 41 -k 50
   35.5    45.4 
   39.4    45.3 
   29.1    36.0 
   28.6    45.6 
   22.4    48.2 
In [104]:
!foldtest.py -f data_files/foldtest/foldtest_example.dat -fmt png -sav -n 300
doing  300  iterations...please be patient.....
0
50
100
150
200
250
81 - 118 Percent Unfolding
range of all bootstrap samples:  72  -  126
1  saved in  foldtest_ge.png
2  saved in  foldtest_st.png
3  saved in  foldtest_ta.png
In [105]:
Image(filename='foldtest_ta.png')
Out[105]:
In [106]:
Image(filename='foldtest_st.png')
Out[106]:
In [107]:
Image(filename='foldtest_ge.png')
Out[107]:

foldtest_magic.py

[notebook version]

In [108]:
!foldtest_magic.py -f data_files/foldtest_magic/sites.txt -fmt png -sav -DM 3 -n 300 -exc
doing  300  iterations...please be patient.....
0
50
100
150
200
250
25 - 102 Percent Unfolding
1  saved in  foldtest_ge.png
2  saved in  foldtest_st.png
3  saved in  foldtest_ta.png
In [109]:
Image(filename='foldtest_ge.png')
Out[109]:
In [110]:
!download_magic.py -WD data_files/foldtest_magic -f data_files/foldtest_magic/magic_contribution_11087.txt
working on:  'er_locations'
2  records written to file  data_files/foldtest_magic/er_locations.txt
er_locations  data put in  data_files/foldtest_magic/er_locations.txt
working on:  'er_sites'
30  records written to file  data_files/foldtest_magic/er_sites.txt
er_sites  data put in  data_files/foldtest_magic/er_sites.txt
working on:  'er_citations'
5  records written to file  data_files/foldtest_magic/er_citations.txt
er_citations  data put in  data_files/foldtest_magic/er_citations.txt
working on:  'pmag_sites'
60  records written to file  data_files/foldtest_magic/pmag_sites.txt
pmag_sites  data put in  data_files/foldtest_magic/pmag_sites.txt
working on:  'pmag_results'
32  records written to file  data_files/foldtest_magic/pmag_results.txt
pmag_results  data put in  data_files/foldtest_magic/pmag_results.txt
working on:  'magic_methods'
9  records written to file  data_files/foldtest_magic/magic_methods.txt
magic_methods  data put in  data_files/foldtest_magic/magic_methods.txt
In [111]:
!foldtest_magic.py -f data_files/foldtest_magic/pmag_sites.txt \
    -fsi data_files/foldtest_magic/er_sites.txt -fmt png -sav -DM 2 -n 300
doing  300  iterations...please be patient.....
0
50
100
150
200
250
91 - 149 Percent Unfolding
1  saved in  foldtest_ge.png
2  saved in  foldtest_st.png
3  saved in  foldtest_ta.png
In [112]:
Image(filename='foldtest_ge.png')
Out[112]:
In [113]:
Image(filename='foldtest_st.png')
Out[113]:
In [114]:
Image(filename='foldtest_ta.png')
Out[114]:

forc_diagram.py

[notebook version]

In [115]:
!forc_diagram.py -f data_files/forc_diagram/conventional_example.forc -sf 3 -sav -fmt png
Image('forc.png')
1  saved in  forc.png
Out[115]:
In [116]:
!gaussian.py -s 3 -n 1000 -m 10. -F data_files/gaussian/gaussian.out
!histplot.py -f data_files/gaussian/gaussian.out -fmt png -sav
hist.png
plot saved in  hist.png
In [117]:
Image(filename='hist.png')
Out[117]:

generic_magic.py

[notebook version]

In [118]:
!generic_magic.py -f data_files/convert_2_magic/generic_magic/generic_magic_example.txt -exp PI
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 23 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 2 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 2 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 2 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 23 records written to measurements file
In [119]:
!gobing.py -f data_files/gobing/gobing_example.txt
  357.8    60.3     4.5   105.7    10.0     4.5    21.0   -27.6 20
In [120]:
!gofish.py -f data_files/gofish/fishrot.out
   10.8    39.6    10     9.8484     59.4     6.3    10.5
In [121]:
!gokent.py -f data_files/gokent/gokent_example.txt
  359.2    55.0     9.3   147.7    30.8     7.8   246.8    14.9 20
In [122]:
!goprinc.py -f data_files/goprinc/tk03.out
0.93863    11.0    58.6 0.04258   226.4    26.5 0.01879   128.3    15.6 20

grab_magic_key.py

[notebook version]

In [123]:
!grab_magic_key.py -f data_files/download_magic/sites.txt -key lat
42.60264
42.60264
42.6026
42.60352
42.6035
42.601040000000005
42.601000000000006
42.73656
42.7366
42.8418
42.8418
42.8657
42.8657
42.92031
42.9203
42.56857
42.49964
42.49962
42.4996
42.500009999999996
42.5
42.52872
42.5287
42.45559
42.4556
42.48923
42.4892
42.461859999999994
42.4619
42.691559999999996
42.65289
42.6529
43.305040000000005
43.305
43.36817
43.36817
43.3682
43.42133
43.4213
43.8859
43.8859
43.8859
43.842729999999996
43.8427
43.53289
43.574940000000005
43.574940000000005
43.5749
44.15663
44.1566
44.18629
42.6026

huji_magic.py

[notebook version]

In [124]:
!huji_magic.py -f data_files/convert_2_magic/HUJI_magic/Massada_AF_HUJI_new_format.txt -LP T
-W- Identical treatments in file data_files/convert_2_magic/HUJI_magic/Massada_AF_HUJI_new_format.txt magfile line 818: specimen M5-119E, treatment 0 ignoring the first. 
-I- done reading file data_files/convert_2_magic/HUJI_magic/Massada_AF_HUJI_new_format.txt
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 616 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 56 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 56 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 29 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 616 records written to measurements file

huji_sample_magic.py

[notebook version]

In [125]:
!huji_sample_magic.py -f data_files/convert_2_magic/HUJI_magic/magdelkrum_datafile.txt
-I- reading in: /Users/nebula/Python/PmagPy/data_files/convert_2_magic/HUJI_magic/magdelkrum_datafile.txt
57  records written to file  /Users/nebula/Python/PmagPy/samples.txt
57  records written to file  /Users/nebula/Python/PmagPy/sites.txt
Sample info saved in  /Users/nebula/Python/PmagPy/samples.txt
Site info saved in  /Users/nebula/Python/PmagPy/sites.txt

hysteresis_magic.py

[notebook version]

In [126]:
# for MagIC data model 3:
!hysteresis_magic.py -WD data_files/hysteresis_magic/ -f measurements.txt \
    -spc IS06a-1  -fmt png -sav
IS06a-1
1  saved in  IS06a-1_hyst.png
2  saved in  IS06a-1_deltaM.png
3  saved in  IS06a-1_DdeltaM.png
4  saved in  IS06a-1_irm.png
In [127]:
Image(filename='IS06a-1_hyst.png')
Out[127]:
In [128]:
Image('IS06a-1_deltaM.png')
Out[128]:
In [129]:
# For MagIC data model 2:
!hysteresis_magic2.py -WD data_files/hysteresis_magic/ -f hysteresis_magic_example.dat \
    -spc IS06a-1  -fmt png -sav
IS06a-1
1  saved in  _IS06a-1_hyst.png
2  saved in  _IS06a-1_deltaM.png
3  saved in  _IS06a-1_DdeltaM.png
5  saved in  _IS06a-1_irm.png
In [130]:
Image(filename='_IS06a-1_hyst.png')
Out[130]:
In [131]:
!hysteresis_magic.py -WD data_files/hysteresis_magic/ -f measurements.txt \
    -spc IS06a-1  -fmt png -sav
IS06a-1
1  saved in  IS06a-1_hyst.png
2  saved in  IS06a-1_deltaM.png
3  saved in  IS06a-1_DdeltaM.png
4  saved in  IS06a-1_irm.png
In [132]:
Image(filename='IS06a-1_hyst.png')
Out[132]:

iodp_dscr_magic.py

In [133]:
!iodp_dscr_magic.py -f data_files/convert_2_magic/IODP_srm_magic/IODP_LIMS_SRMdiscrete_344_1414A.csv
processing:  /Users/nebula/Python/PmagPy/data_files/convert_2_magic/IODP_srm_magic/IODP_LIMS_SRMdiscrete_344_1414A.csv
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 112 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 56 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 32 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 1 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 112 records written to measurements file

iodp_jr6_magic.py

In [134]:
!iodp_jr6_magic.py -f data_files/convert_2_magic/IODP_jr6_magic/test.jr6
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 1 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 1 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 1 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 1 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 1 records written to measurements file

iodp_srm_magic.py

In [135]:
!iodp_srm_magic.py -f data_files/convert_2_magic/iodp_srm_magic/SRM_318_U1359_B_A.csv
processing: data_files/convert_2_magic/iodp_srm_magic/SRM_318_U1359_B_A.csv
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
No dec or inc found for specimen 318-U1359B-003H_2A-0.00, skipping
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 6275 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 3233 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 22 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 1 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 6275 records written to measurements file
In [136]:
!igrf.py -ages -3000 1950 50 -loc 33 -117 -mod pfm9k -plt -fmt png -sav
Figure saved as:  igrf.png
In [137]:
Image(filename='igrf.png')
Out[137]:

install_etopo.py

In [138]:
# install high resolution maps, only used for Basemap
!install_etopo.py
-E- Could not import the basemap module...
In [139]:
!incfish.py -f data_files/incfish/incfish_example_inc.dat
   57.1    61.0  100     92.9    13.9     1.0

irmaq_magic.py

[notebook version]

In [140]:
!sio_magic.py -f data_files/irmaq_magic/U1359A_IRM_coil2.txt -LP I -V 2 \
    -WD data_files/irmaq_magic/ -F U1359A_IRM_coil2.magic -loc U1359A -spc 0 -ncn 5 \
    -Fsp coil2_specimens.txt -Fsa coil2_samples.txt -Fsi coil2_sites.txt -Flo coil2_locations.txt
    
!sio_magic.py -f data_files/irmaq_magic/U1359A_IRM_coil3.txt -LP I -V 3 \
    -WD data_files/irmaq_magic/ -F U1359A_IRM_coil3.magic -loc U1359A -spc 0 -ncn 5 \
    -Fsp coil3_specimens.txt -Fsa coil3_samples.txt -Fsi coil3_sites.txt -Flo coil3_locations.txt

!combine_magic.py -F data_files/irmaq_magic/measurements.txt \
    -f data_files/irmaq_magic/U1359A_IRM_coil2.magic \
    data_files/irmaq_magic/U1359A_IRM_coil3.magic -dm 3
    
!combine_magic.py -F measurements.txt -WD data_files/irmaq_magic \
    -f U1359A_IRM_coil2.magic U1359A_IRM_coil3.magic -dm 3
    
!combine_magic.py -F specimens.txt -WD data_files/irmaq_magic \
    -f coil2_specimens.txt coil3_specimens.txt
    
!combine_magic.py -F samples.txt -WD data_files/irmaq_magic \
    -f coil2_samples.txt coil3_samples.txt
    
!combine_magic.py -F sites.txt -WD data_files/irmaq_magic \
    -f coil2_sites.txt coil3_sites.txt
    
!combine_magic.py -F locations.txt -WD data_files/irmaq_magic \
    -f coil2_locations.txt coil3_locations.txt
    
    
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 536 records written to measurements file
-I- writing specimens records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/coil2_specimens.txt
-I- 49 records written to specimens file
-I- writing samples records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/coil2_samples.txt
-I- 49 records written to samples file
-I- writing sites records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/coil2_sites.txt
-I- 49 records written to sites file
-I- writing locations records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/coil2_locations.txt
-I- 1 records written to locations file
-I- writing measurements records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/U1359A_IRM_coil2.magic
-I- 536 records written to measurements file
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 23 records written to measurements file
-I- writing specimens records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/coil3_specimens.txt
-I- 14 records written to specimens file
-I- writing samples records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/coil3_samples.txt
-I- 14 records written to samples file
-I- writing sites records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/coil3_sites.txt
-I- 14 records written to sites file
-I- writing locations records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/coil3_locations.txt
-I- 1 records written to locations file
-I- writing measurements records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/U1359A_IRM_coil3.magic
-I- 23 records written to measurements file
Using default arguments for: -A, -WD, -ID, -Fsa, -Fsi
-I- Using online data model
-I- Using online data model
-I- overwriting /Users/nebula/Python/PmagPy/data_files/irmaq_magic/measurements.txt
-I- 559 records written to measurements file
Using default arguments for: -A, -ID, -Fsa, -Fsi
-I- Using online data model
-I- Using online data model
-I- overwriting /Users/nebula/Python/PmagPy/data_files/irmaq_magic/measurements.txt
-I- 559 records written to measurements file
Using default arguments for: -A, -ID, -Fsa, -Fsi, -dm
-I- Using online data model
-I- Using online data model
-I- writing specimens records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/specimens.txt
-I- 63 records written to specimens file
Using default arguments for: -A, -ID, -Fsa, -Fsi, -dm
-I- Using online data model
-I- Using online data model
-I- writing samples records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/samples.txt
-I- 63 records written to samples file
Using default arguments for: -A, -ID, -Fsa, -Fsi, -dm
-I- Using online data model
-I- Using online data model
-I- writing sites records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/sites.txt
-I- 63 records written to sites file
Using default arguments for: -A, -ID, -Fsa, -Fsi, -dm
-I- Using online data model
-I- Using online data model
-I- writing locations records to /Users/nebula/Python/PmagPy/data_files/irmaq_magic/locations.txt
-I- 1 records written to locations file
In [141]:
!irmaq_magic.py -f data_files/irmaq_magic/measurements.txt -fmt png -sav -DM 3
-W- You are trying to plot measurements by location
    By default, this information is not available in your measurement file.
    Trying to acquire this information from /Users/nebula/Python/PmagPy/data_files/irmaq_magic
-I- Using online data model
-I- Found location information, continuing with plotting
U1359A
1  saved in  U1359A_LP-IRM.png
In [142]:
Image("U1359A_LP-IRM.png")
Out[142]:

irmaq_magic.py (data model 2)

In [143]:
!sio_magic2.py -f data_files/irmaq_magic/U1359A_IRM_coil2.txt -LP I -V 2 \
    -F data_files/irmaq_magic/U1359A_IRM_coil2.magic -loc U1359A -spc 0 -ncn 5
!sio_magic2.py -f data_files/irmaq_magic/U1359A_IRM_coil3.txt -LP I -V 3 \
    -F data_files/irmaq_magic/U1359A_IRM_coil3.magic -loc U1359A -spc 0 -ncn 5
!combine_magic.py -F data_files/irmaq_magic/magic_measurements.txt \
    -f data_files/irmaq_magic/U1359A_IRM_coil2.magic \
    data_files/irmaq_magic/U1359A_IRM_coil3.magic -dm 2
536  records written to file  data_files/irmaq_magic/U1359A_IRM_coil2.magic
results put in  data_files/irmaq_magic/U1359A_IRM_coil2.magic
23  records written to file  data_files/irmaq_magic/U1359A_IRM_coil3.magic
results put in  data_files/irmaq_magic/U1359A_IRM_coil3.magic
Using default arguments for: -A, -WD, -ID, -Fsa, -Fsi
File  ./data_files/irmaq_magic/U1359A_IRM_coil2.magic  read in with  536  records
File  ./data_files/irmaq_magic/U1359A_IRM_coil3.magic  read in with  23  records
559  records written to file  ./data_files/irmaq_magic/magic_measurements.txt
All records stored in  ./data_files/irmaq_magic/magic_measurements.txt
In [144]:
!irmaq_magic.py -f data_files/irmaq_magic/magic_measurements.txt -fmt png -sav -DM 2
U1359A
1  saved in  U1359A_LP-IRM.png
In [145]:
Image(filename='U1359A_LP-IRM.png')
Out[145]:

jr6_jr6_magic.py

[notebook version]

In [146]:
!jr6_jr6_magic.py -f data_files/convert_2_magic/JR6_magic/AF.jr6
.
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 655 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 57 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 17 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 10 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 655 records written to measurements file

jr6_txt_magic.py

[notebook version]

In [147]:
!jr6_txt_magic.py -f data_files/convert_2_magic/JR6_magic/AF.txt
-I- Using less strict decoding for /Users/nebula/Python/PmagPy/data_files/convert_2_magic/JR6_magic/AF.txt, output may have formatting errors
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 655 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 57 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 17 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 10 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 655 records written to measurements file

k15_magic.py

[notebook version]

In [148]:
!k15_magic.py -WD data_files/k15_magic  -spc 0 -f data_files/k15_s/k15_example.dat -loc "Troodos Ophiolite" 
Using default arguments for: -F, -A, -ID, -Fsa, -Fsi, -Fa, -Fr, -ncn, -DM
8  records written to file  /Users/nebula/Python/PmagPy/data_files/k15_magic/samples.txt
48  records written to file  /Users/nebula/Python/PmagPy/data_files/k15_magic/specimens.txt
120  records written to file  /Users/nebula/Python/PmagPy/data_files/k15_magic/measurements.txt
Data saved to: /Users/nebula/Python/PmagPy/data_files/k15_magic/measurements.txt, /Users/nebula/Python/PmagPy/data_files/k15_magic/specimens.txt, /Users/nebula/Python/PmagPy/data_files/k15_magic/samples.txt
In [149]:
!k15_s.py -f data_files/k15_s/k15_example.dat
0.33146986 0.33413991 0.33439023 0.00075095 -0.00083439 -0.00016688 0.00008618
0.33335925 0.33335925 0.33328149 -0.00155521 -0.00132193 0.00116641 0.00017193
0.33097634 0.33573565 0.33328801 0.00163177 0.00013598 0.00000000 0.00018131
0.33150029 0.33465420 0.33384551 -0.00064696 -0.00056609 -0.00048522 0.00014863
0.33121986 0.33521197 0.33356816 -0.00046966 -0.00046966 -0.00086104 0.00018376
0.33179570 0.33405602 0.33414828 -0.00009226 -0.00004613 -0.00027677 0.00010474
0.33243163 0.33439898 0.33316939 0.00106564 0.00032789 0.00000000 0.00017624
0.33175478 0.33512715 0.33311808 0.00078928 0.00000000 -0.00007175 0.00011116

kly4s_magic.py

[notebook version]

In [150]:
!kly4s_magic.py -f data_files/convert_2_magic/kly4s_magic/KLY4S_magic_example.dat
Using default arguments for: -F, -A, -WD, -ID, -Fsa, -Fsi, -fad, -fsa, -fsp, -Fsp, -Fa, -ocn, -usr, -loc, -ins, -spc, -ncn, -DM
anisotropy data added to specimen records
52  records written to file  ./specimens.txt
specimen information written to new file: ./specimens.txt
26  records written to file  ./measurements.txt
measurement data saved in  ./measurements.txt
26  records written to file  samples.txt
26  records written to file  sites.txt

ldeo_magic.py

[notebook version]

In [151]:
!ldeo_magic.py -f data_files/convert_2_magic/LDEO_magic/ldeo_magic_example.dat
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 35 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 35 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 35 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 35 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 35 records written to measurements file

livdb_magic.py

[notebook version]

In [152]:
# is a GUI and doesn't work in a notebook
# see _PmagPy-nb.ipynb for how to use convert.livdb

lnp_magic.py

[notebook version]

In [153]:
!lnp_magic.py -f data_files/lnp_magic/specimens.txt -crd g -fmt png -sav -fsa data_files/lnp_magic/samples.txt
-I- Using online data model
sv01
Site lines planes  kappa   a95   dec   inc
sv01 0  5     286      6.6    179.0    -54.3  4.9948 
% tilt correction:  0
1  saved in  sv01_g_eqarea.png
sv02
Site lines planes  kappa   a95   dec   inc
sv02 4  2     113      6.6    338.8     38.6  5.9647 
% tilt correction:  0
1  saved in  sv02_g_eqarea.png
sv03
Site lines planes  kappa   a95   dec   inc
sv03 5  3     108      5.5    344.0     53.1  7.9491 
% tilt correction:  0
1  saved in  sv03_g_eqarea.png
sv04
Site lines planes  kappa   a95   dec   inc
sv04 5  0     286      4.5    346.9     50.7  4.9860 
% tilt correction:  0
1  saved in  sv04_g_eqarea.png
sv05
Site lines planes  kappa   a95   dec   inc
sv05 5  3     165      4.5    164.1    -51.3  7.9667 
% tilt correction:  0
1  saved in  sv05_g_eqarea.png
sv06
Site lines planes  kappa   a95   dec   inc
sv06 2  3      81      9.7    351.4    -32.0  4.9691 
% tilt correction:  0
1  saved in  sv06_g_eqarea.png
sv07
Site lines planes  kappa   a95   dec   inc
sv07 7  1     318      3.1    350.3     61.8  7.9796 
% tilt correction:  0
1  saved in  sv07_g_eqarea.png
sv08
Site lines planes  kappa   a95   dec   inc
sv08 7  0     151      4.9    165.7    -46.1  6.9603 
% tilt correction:  0
1  saved in  sv08_g_eqarea.png
sv09
Site lines planes  kappa   a95   dec   inc
sv09 5  0      10     26.2    251.6    -57.1  4.5791 
% tilt correction:  0
1  saved in  sv09_g_eqarea.png
sv10
Site lines planes  kappa   a95   dec   inc
sv10 0  5      65     13.9    188.9    -47.3  4.9770 
% tilt correction:  0
1  saved in  sv10_g_eqarea.png
sv11
Site lines planes  kappa   a95   dec   inc
sv11 2  2     116     10.0    193.6    -43.2  3.9827 
% tilt correction:  0
1  saved in  sv11_g_eqarea.png
sv12
skipping site - not enough data with specified coordinate system
sv13
skipping site - not enough data with specified coordinate system
sv15
Site lines planes  kappa   a95   dec   inc
sv15 6  0     175      5.1    352.8     25.5  5.9714 
% tilt correction:  0
1  saved in  sv15_g_eqarea.png
sv16
Site lines planes  kappa   a95   dec   inc
sv16 4  1     166      6.1    356.0     24.1  4.9789 
% tilt correction:  0
1  saved in  sv16_g_eqarea.png
sv17
skipping site - not enough data with specified coordinate system
sv18
Site lines planes  kappa   a95   dec   inc
sv18 5  0     704      2.9    192.8    -55.9  4.9943 
% tilt correction:  0
1  saved in  sv18_g_eqarea.png
sv19
skipping site - not enough data with specified coordinate system
sv20
skipping site - not enough data with specified coordinate system
sv21
skipping site - not enough data with specified coordinate system
sv22
skipping site - not enough data with specified coordinate system
sv23
Site lines planes  kappa   a95   dec   inc
sv23 4  1     464      3.7     19.5     29.0  4.9925 
% tilt correction:  0
1  saved in  sv23_g_eqarea.png
sv24
Site lines planes  kappa   a95   dec   inc
sv24 7  0     109      5.8    339.2     63.7  6.9452 
% tilt correction:  0
1  saved in  sv24_g_eqarea.png
sv25
skipping site - not enough data with specified coordinate system
sv26
Site lines planes  kappa   a95   dec   inc
sv26 4  2     109      6.7    159.0    -69.1  5.9633 
% tilt correction:  0
1  saved in  sv26_g_eqarea.png
sv27
Site lines planes  kappa   a95   dec   inc
sv27 4  1     241      5.1    354.0     55.9  4.9854 
% tilt correction:  0
1  saved in  sv27_g_eqarea.png
sv28
skipping site - not enough data with specified coordinate system
sv29
skipping site - not enough data with specified coordinate system
sv30
skipping site - not enough data with specified coordinate system
sv31
Site lines planes  kappa   a95   dec   inc
sv31 5  0     394      3.9     12.7     46.2  4.9898 
% tilt correction:  0
1  saved in  sv31_g_eqarea.png
sv32
Site lines planes  kappa   a95   dec   inc
sv32 5  0     384      3.9    342.9     60.3  4.9896 
% tilt correction:  0
1  saved in  sv32_g_eqarea.png
sv50
Site lines planes  kappa   a95   dec   inc
sv50 2  1       1    180.0    266.8    -40.9  1.9606 
% tilt correction:  0
1  saved in  sv50_g_eqarea.png
sv51
Site lines planes  kappa   a95   dec   inc
sv51 4  0       2     84.3    207.2    -39.4  2.6222 
% tilt correction:  0
1  saved in  sv51_g_eqarea.png
sv52
Site lines planes  kappa   a95   dec   inc
sv52 4  0     199      6.5    182.7    -54.9  3.9850 
% tilt correction:  0
1  saved in  sv52_g_eqarea.png
sv53
Site lines planes  kappa   a95   dec   inc
sv53 3  0       3     86.4    178.0    -26.5  2.3622 
% tilt correction:  0
1  saved in  sv53_g_eqarea.png
sv54
Site lines planes  kappa   a95   dec   inc
sv54 5  0      30     14.1    175.3    -46.7  4.8684 
% tilt correction:  0
1  saved in  sv54_g_eqarea.png
sv55
Site lines planes  kappa   a95   dec   inc
sv55 4  0     409      4.5    181.2    -45.0  3.9927 
% tilt correction:  0
1  saved in  sv55_g_eqarea.png
sv56
Site lines planes  kappa   a95   dec   inc
sv56 4  1       3     50.1    171.1    -68.8  3.9527 
% tilt correction:  0
1  saved in  sv56_g_eqarea.png
sv57
Site lines planes  kappa   a95   dec   inc
sv57 5  0      20     17.8    199.6    -46.4  4.7950 
% tilt correction:  0
1  saved in  sv57_g_eqarea.png
sv58
Site lines planes  kappa   a95   dec   inc
sv58 4  0     570      3.9    182.0    -62.3  3.9947 
% tilt correction:  0
1  saved in  sv58_g_eqarea.png
sv59
Site lines planes  kappa   a95   dec   inc
sv59 4  0    1128      2.7    178.8    -51.3  3.9973 
% tilt correction:  0
1  saved in  sv59_g_eqarea.png
sv60
skipping site - not enough data with specified coordinate system
sv61
Site lines planes  kappa   a95   dec   inc
sv61 3  1       7     39.5      2.9     77.8  3.6408 
% tilt correction:  0
1  saved in  sv61_g_eqarea.png
sv62
Site lines planes  kappa   a95   dec   inc
sv62 0  3     308     38.3    133.7    -52.3  2.9984 
% tilt correction:  0
1  saved in  sv62_g_eqarea.png
sv63
Site lines planes  kappa   a95   dec   inc
sv63 4  0     489      4.2    351.5     45.1  3.9939 
% tilt correction:  0
1  saved in  sv63_g_eqarea.png
sv64
Site lines planes  kappa   a95   dec   inc
sv64 6  0     172      5.1    170.4    -51.6  5.9710 
% tilt correction:  0
1  saved in  sv64_g_eqarea.png
sv65
Site lines planes  kappa   a95   dec   inc
sv65 4  1      90      8.3     31.0     54.4  4.9611 
% tilt correction:  0
1  saved in  sv65_g_eqarea.png
In [154]:
Image(filename='sv01_g_eqarea.png')
Out[154]:
In [155]:
os.remove('sv01_g_eqarea.png')
In [156]:
!download_magic.py  -WD data_files/lnp_magic -ID data_files/lnp_magic -f zmab0001193tmp02.txt
working on:  'er_locations\r'
1  records written to file  data_files/lnp_magic/er_locations.txt
  data put in  data_files/lnp_magic/er_locations.txt
working on:  'er_sites\r'
47  records written to file  data_files/lnp_magic/er_sites.txt
  data put in  data_files/lnp_magic/er_sites.txt
working on:  'er_samples\r'
521  records written to file  data_files/lnp_magic/er_samples.txt
  data put in  data_files/lnp_magic/er_samples.txt
working on:  'er_specimens\r'
306  records written to file  data_files/lnp_magic/er_specimens.txt
  data put in  data_files/lnp_magic/er_specimens.txt
working on:  'er_ages\r'
15  records written to file  data_files/lnp_magic/er_ages.txt
  data put in  data_files/lnp_magic/er_ages.txt
working on:  'er_citations'
11  records written to file  data_files/lnp_magic/er_citations.txt
er_citations  data put in  data_files/lnp_magic/er_citations.txt
working on:  'magic_measurements\r'
4142  records written to file  data_files/lnp_magic/magic_measurements.txt
  data put in  data_files/lnp_magic/magic_measurements.txt
working on:  'pmag_specimens\r'
196  records written to file  data_files/lnp_magic/pmag_specimens.txt
  data put in  data_files/lnp_magic/pmag_specimens.txt
working on:  'pmag_samples\r'
189  records written to file  data_files/lnp_magic/pmag_samples.txt
  data put in  data_files/lnp_magic/pmag_samples.txt
working on:  'pmag_sites\r'
35  records written to file  data_files/lnp_magic/pmag_sites.txt
  data put in  data_files/lnp_magic/pmag_sites.txt
working on:  'pmag_results\r'
17  records written to file  data_files/lnp_magic/pmag_results.txt
  data put in  data_files/lnp_magic/pmag_results.txt
working on:  'pmag_criteria\r'
7  records written to file  data_files/lnp_magic/pmag_criteria.txt
  data put in  data_files/lnp_magic/pmag_criteria.txt
working on:  'magic_methods\r'
24  records written to file  data_files/lnp_magic/magic_methods.txt
  data put in  data_files/lnp_magic/magic_methods.txt
In [157]:
!lnp_magic.py -f data_files/lnp_magic/pmag_specimens.txt -crd g -fmt png -sav -DM 2
sv01
Site lines planes  kappa   a95   dec   inc
sv01 0  5     286      6.6    179.0    -54.3  4.9948 
% tilt correction:  0
1  saved in  sv01_g_eqarea.png
sv02
Site lines planes  kappa   a95   dec   inc
sv02 4  2     113      6.6    338.8     38.6  5.9647 
% tilt correction:  0
1  saved in  sv02_g_eqarea.png
sv03
Site lines planes  kappa   a95   dec   inc
sv03 5  3     108      5.5    344.0     53.1  7.9491 
% tilt correction:  0
1  saved in  sv03_g_eqarea.png
sv04
Site lines planes  kappa   a95   dec   inc
sv04 5  0     286      4.5    346.9     50.7  4.9860 
% tilt correction:  0
1  saved in  sv04_g_eqarea.png
sv05
Site lines planes  kappa   a95   dec   inc
sv05 5  3     165      4.5    164.1    -51.3  7.9667 
% tilt correction:  0
1  saved in  sv05_g_eqarea.png
sv06
Site lines planes  kappa   a95   dec   inc
sv06 2  3      81      9.7    351.4    -32.0  4.9691 
% tilt correction:  0
1  saved in  sv06_g_eqarea.png
sv07
Site lines planes  kappa   a95   dec   inc
sv07 7  1     318      3.1    350.3     61.8  7.9796 
% tilt correction:  0
1  saved in  sv07_g_eqarea.png
sv08
Site lines planes  kappa   a95   dec   inc
sv08 7  0     151      4.9    165.7    -46.1  6.9603 
% tilt correction:  0
1  saved in  sv08_g_eqarea.png
sv09
Site lines planes  kappa   a95   dec   inc
sv09 5  0      10     26.2    251.6    -57.1  4.5791 
% tilt correction:  0
1  saved in  sv09_g_eqarea.png
sv10
Site lines planes  kappa   a95   dec   inc
sv10 0  5      65     13.9    188.9    -47.3  4.9770 
% tilt correction:  0
1  saved in  sv10_g_eqarea.png
sv11
Site lines planes  kappa   a95   dec   inc
sv11 2  2     116     10.0    193.6    -43.2  3.9827 
% tilt correction:  0
1  saved in  sv11_g_eqarea.png
sv12
skipping site - not enough data with specified coordinate system
sv13
skipping site - not enough data with specified coordinate system
sv15
Site lines planes  kappa   a95   dec   inc
sv15 6  0     175      5.1    352.8     25.5  5.9714 
% tilt correction:  0
1  saved in  sv15_g_eqarea.png
sv16
Site lines planes  kappa   a95   dec   inc
sv16 4  1     166      6.1    356.0     24.1  4.9789 
% tilt correction:  0
1  saved in  sv16_g_eqarea.png
sv17
skipping site - not enough data with specified coordinate system
sv18
Site lines planes  kappa   a95   dec   inc
sv18 5  0     704      2.9    192.8    -55.9  4.9943 
% tilt correction:  0
1  saved in  sv18_g_eqarea.png
sv19
skipping site - not enough data with specified coordinate system
sv20
skipping site - not enough data with specified coordinate system
sv21
skipping site - not enough data with specified coordinate system
sv22
skipping site - not enough data with specified coordinate system
sv23
Site lines planes  kappa   a95   dec   inc
sv23 4  1     464      3.7     19.5     29.0  4.9925 
% tilt correction:  0
1  saved in  sv23_g_eqarea.png
sv24
Site lines planes  kappa   a95   dec   inc
sv24 7  0     109      5.8    339.2     63.7  6.9452 
% tilt correction:  0
1  saved in  sv24_g_eqarea.png
sv25
skipping site - not enough data with specified coordinate system
sv26
Site lines planes  kappa   a95   dec   inc
sv26 4  2     109      6.7    159.0    -69.1  5.9633 
% tilt correction:  0
1  saved in  sv26_g_eqarea.png
sv27
Site lines planes  kappa   a95   dec   inc
sv27 4  1     241      5.1    354.0     55.9  4.9854 
% tilt correction:  0
1  saved in  sv27_g_eqarea.png
sv28
skipping site - not enough data with specified coordinate system
sv30
skipping site - not enough data with specified coordinate system
sv31
Site lines planes  kappa   a95   dec   inc
sv31 5  0     394      3.9     12.7     46.2  4.9898 
% tilt correction:  0
1  saved in  sv31_g_eqarea.png
sv32
Site lines planes  kappa   a95   dec   inc
sv32 5  0     384      3.9    342.9     60.3  4.9896 
% tilt correction:  0
1  saved in  sv32_g_eqarea.png
sv50
Site lines planes  kappa   a95   dec   inc
sv50 2  1       1    180.0    266.8    -40.9  1.9606 
% tilt correction:  0
1  saved in  sv50_g_eqarea.png
sv51
Site lines planes  kappa   a95   dec   inc
sv51 4  0       2     84.3    207.2    -39.4  2.6222 
% tilt correction:  0
1  saved in  sv51_g_eqarea.png
sv52
Site lines planes  kappa   a95   dec   inc
sv52 4  0     199      6.5    182.7    -54.9  3.9850 
% tilt correction:  0
1  saved in  sv52_g_eqarea.png
sv53
Site lines planes  kappa   a95   dec   inc
sv53 3  0       3     86.4    178.0    -26.5  2.3622 
% tilt correction:  0
1  saved in  sv53_g_eqarea.png
sv54
Site lines planes  kappa   a95   dec   inc
sv54 5  0      30     14.1    175.3    -46.7  4.8684 
% tilt correction:  0
1  saved in  sv54_g_eqarea.png
sv55
Site lines planes  kappa   a95   dec   inc
sv55 4  0     409      4.5    181.2    -45.0  3.9927 
% tilt correction:  0
1  saved in  sv55_g_eqarea.png
sv56
Site lines planes  kappa   a95   dec   inc
sv56 4  1       3     50.1    171.1    -68.8  3.9527 
% tilt correction:  0
1  saved in  sv56_g_eqarea.png
sv57
Site lines planes  kappa   a95   dec   inc
sv57 5  0      20     17.8    199.6    -46.4  4.7950 
% tilt correction:  0
1  saved in  sv57_g_eqarea.png
sv58
Site lines planes  kappa   a95   dec   inc
sv58 4  0     570      3.9    182.0    -62.3  3.9947 
% tilt correction:  0
1  saved in  sv58_g_eqarea.png
sv59
Site lines planes  kappa   a95   dec   inc
sv59 4  0    1128      2.7    178.8    -51.3  3.9973 
% tilt correction:  0
1  saved in  sv59_g_eqarea.png
sv60
skipping site - not enough data with specified coordinate system
sv61
Site lines planes  kappa   a95   dec   inc
sv61 3  1       7     39.5      2.9     77.8  3.6408 
% tilt correction:  0
1  saved in  sv61_g_eqarea.png
sv62
Site lines planes  kappa   a95   dec   inc
sv62 0  3     308     38.3    133.7    -52.3  2.9984 
% tilt correction:  0
1  saved in  sv62_g_eqarea.png
sv63
Site lines planes  kappa   a95   dec   inc
sv63 4  0     489      4.2    351.5     45.1  3.9939 
% tilt correction:  0
1  saved in  sv63_g_eqarea.png
sv64
Site lines planes  kappa   a95   dec   inc
sv64 6  0     172      5.1    170.4    -51.6  5.9710 
% tilt correction:  0
1  saved in  sv64_g_eqarea.png
sv65
Site lines planes  kappa   a95   dec   inc
sv65 4  1      90      8.3     31.0     54.4  4.9611 
% tilt correction:  0
1  saved in  sv65_g_eqarea.png
In [158]:
Image(filename='sv01_g_eqarea.png')
Out[158]:

lowes.py doesn't work from within a notebook. yet.

In [159]:
!lowrie.py -f data_files/lowrie/lowrie_example.dat -fmt png -sav
-I- Using less strict decoding for data_files/lowrie/lowrie_example.dat, output may have formatting errors
318-U1359A-002H-1-W-109
1  saved in  lowrie__318-U1359A-002H-1-W-109_.png
318-U1359A-002H-4-W-65
1  saved in  lowrie__318-U1359A-002H-4-W-65_.png
318-U1359A-002H-6-W-7
1  saved in  lowrie__318-U1359A-002H-6-W-7_.png
318-U1359A-003H-2-W-37
1  saved in  lowrie__318-U1359A-003H-2-W-37_.png
318-U1359A-003H-6-W-66
1  saved in  lowrie__318-U1359A-003H-6-W-66_.png
318-U1359A-004H-2-W-18
1  saved in  lowrie__318-U1359A-004H-2-W-18_.png
318-U1359A-004H-2-W-44
1  saved in  lowrie__318-U1359A-004H-2-W-44_.png
318-U1359A-004H-2-W-130
1  saved in  lowrie__318-U1359A-004H-2-W-130_.png
318-U1359A-004H-3-W-100
1  saved in  lowrie__318-U1359A-004H-3-W-100_.png
318-U1359A-004H-3-W-145
1  saved in  lowrie__318-U1359A-004H-3-W-145_.png
318-U1359A-004H-4-W-102
1  saved in  lowrie__318-U1359A-004H-4-W-102_.png
318-U1359A-004H-4-W-120
1  saved in  lowrie__318-U1359A-004H-4-W-120_.png
318-U1359A-004H-5-W-139
1  saved in  lowrie__318-U1359A-004H-5-W-139_.png
318-U1359A-006H-2-W-95
1  saved in  lowrie__318-U1359A-006H-2-W-95_.png
318-U1359A-006H-6-W-22
1  saved in  lowrie__318-U1359A-006H-6-W-22_.png
318-U1359A-007H-1-W-54
1  saved in  lowrie__318-U1359A-007H-1-W-54_.png
318-U1359A-007H-2-W-125
1  saved in  lowrie__318-U1359A-007H-2-W-125_.png
318-U1359A-007H-3-W-46
1  saved in  lowrie__318-U1359A-007H-3-W-46_.png
318-U1359A-009H-6-W-31
1  saved in  lowrie__318-U1359A-009H-6-W-31_.png
318-U1359A-010H-2-W-73
1  saved in  lowrie__318-U1359A-010H-2-W-73_.png
318-U1359A-010H-4-W-37
1  saved in  lowrie__318-U1359A-010H-4-W-37_.png
318-U1359A-010H-6-W-65
1  saved in  lowrie__318-U1359A-010H-6-W-65_.png
318-U1359A-011H-3-W-70
1  saved in  lowrie__318-U1359A-011H-3-W-70_.png
318-U1359A-012H-1-W-104
1  saved in  lowrie__318-U1359A-012H-1-W-104_.png
318-U1359A-012H-5-W-70
1  saved in  lowrie__318-U1359A-012H-5-W-70_.png
318-U1359A-013H-4-W-89
1  saved in  lowrie__318-U1359A-013H-4-W-89_.png
318-U1359A-013H-6-W-88
1  saved in  lowrie__318-U1359A-013H-6-W-88_.png
318-U1359A-014H-2-W-60
1  saved in  lowrie__318-U1359A-014H-2-W-60_.png
318-U1359A-014H-6-W-13
1  saved in  lowrie__318-U1359A-014H-6-W-13_.png
318-U1359A-015H-2-W-56
1  saved in  lowrie__318-U1359A-015H-2-W-56_.png
318-U1359A-015H-4-W-83
1  saved in  lowrie__318-U1359A-015H-4-W-83_.png
318-U1359A-018X-6-W-57
1  saved in  lowrie__318-U1359A-018X-6-W-57_.png
318-U1359A-022X-2-W-95
1  saved in  lowrie__318-U1359A-022X-2-W-95_.png
In [160]:
Image(filename='lowrie__318-U1359A-002H-1-W-109_.png')
Out[160]:

lowrie_magic.py

[notebook version]

In [161]:
!lowrie_magic.py -f data_files/lowrie_magic/measurements.txt -fmt png -sav
/Users/nebula/Python/PmagPy/data_files/lowrie_magic/measurements.txt
318-U1361A-007H-1-W-100a
1  saved in  lowrie__318-U1361A-007H-1-W-100a_.png
318-U1361A-007H-3-W-135a
1  saved in  lowrie__318-U1361A-007H-3-W-135a_.png
318-U1361A-007H-4-W-42a
1  saved in  lowrie__318-U1361A-007H-4-W-42a_.png
318-U1361A-007H-7-W-20a
1  saved in  lowrie__318-U1361A-007H-7-W-20a_.png
318-U1361A-008H-1-W-73a
1  saved in  lowrie__318-U1361A-008H-1-W-73a_.png
318-U1361A-008H-3-W-102a
1  saved in  lowrie__318-U1361A-008H-3-W-102a_.png
318-U1361A-008H-4-W-78a
1  saved in  lowrie__318-U1361A-008H-4-W-78a_.png
318-U1361A-008H-5-W-67a
1  saved in  lowrie__318-U1361A-008H-5-W-67a_.png
318-U1361A-008H-6-W-83a
1  saved in  lowrie__318-U1361A-008H-6-W-83a_.png
318-U1361A-008H-7-W-28a
1  saved in  lowrie__318-U1361A-008H-7-W-28a_.png
318-U1361A-009H-1-W-94a
1  saved in  lowrie__318-U1361A-009H-1-W-94a_.png
318-U1361A-009H-2-W-77a
1  saved in  lowrie__318-U1361A-009H-2-W-77a_.png
318-U1361A-009H-3-W-63a
1  saved in  lowrie__318-U1361A-009H-3-W-63a_.png
318-U1361A-009H-6-W-51a
1  saved in  lowrie__318-U1361A-009H-6-W-51a_.png
318-U1361A-009H-7-W-53a
1  saved in  lowrie__318-U1361A-009H-7-W-53a_.png
318-U1361A-010H-1-W-86a
1  saved in  lowrie__318-U1361A-010H-1-W-86a_.png
318-U1361A-010H-2-W-88a
1  saved in  lowrie__318-U1361A-010H-2-W-88a_.png
318-U1361A-010H-3-W-51a
1  saved in  lowrie__318-U1361A-010H-3-W-51a_.png
318-U1361A-010H-4-W-81a
1  saved in  lowrie__318-U1361A-010H-4-W-81a_.png
318-U1361A-010H-5-W-58a
1  saved in  lowrie__318-U1361A-010H-5-W-58a_.png
318-U1361A-010H-6-W-16a
1  saved in  lowrie__318-U1361A-010H-6-W-16a_.png
318-U1361A-010H-7-W-17a
1  saved in  lowrie__318-U1361A-010H-7-W-17a_.png
318-U1361A-011H-1-W-75a
1  saved in  lowrie__318-U1361A-011H-1-W-75a_.png
318-U1361A-011H-2-W-95a
1  saved in  lowrie__318-U1361A-011H-2-W-95a_.png
318-U1361A-011H-3-W-82a
1  saved in  lowrie__318-U1361A-011H-3-W-82a_.png
318-U1361A-011H-4-W-99a
1  saved in  lowrie__318-U1361A-011H-4-W-99a_.png
318-U1361A-011H-5-W-92a
1  saved in  lowrie__318-U1361A-011H-5-W-92a_.png
318-U1361A-011H-6-W-77a
1  saved in  lowrie__318-U1361A-011H-6-W-77a_.png
318-U1361A-012H-4-W-91a
1  saved in  lowrie__318-U1361A-012H-4-W-91a_.png
318-U1361A-012H-5-W-122a
1  saved in  lowrie__318-U1361A-012H-5-W-122a_.png
318-U1361A-012H-7-W-43a
1  saved in  lowrie__318-U1361A-012H-7-W-43a_.png
318-U1361A-013H-1-W-102a
1  saved in  lowrie__318-U1361A-013H-1-W-102a_.png
318-U1361A-013H-2-W-70a
1  saved in  lowrie__318-U1361A-013H-2-W-70a_.png
318-U1361A-013H-4-W-118a
1  saved in  lowrie__318-U1361A-013H-4-W-118a_.png
318-U1361A-013H-5-W-95a
1  saved in  lowrie__318-U1361A-013H-5-W-95a_.png
318-U1361A-013H-6-W-89a
1  saved in  lowrie__318-U1361A-013H-6-W-89a_.png
318-U1361A-014H-2-W-87a
1  saved in  lowrie__318-U1361A-014H-2-W-87a_.png
318-U1361A-014H-3-W-115a
1  saved in  lowrie__318-U1361A-014H-3-W-115a_.png
318-U1361A-014H-4-W-110a
1  saved in  lowrie__318-U1361A-014H-4-W-110a_.png
318-U1361A-014H-5-W-113a
1  saved in  lowrie__318-U1361A-014H-5-W-113a_.png
318-U1361A-014H-6-W-88a
1  saved in  lowrie__318-U1361A-014H-6-W-88a_.png
318-U1361A-015H-1-W-110a
1  saved in  lowrie__318-U1361A-015H-1-W-110a_.png
318-U1361A-015H-2-W-59a
1  saved in  lowrie__318-U1361A-015H-2-W-59a_.png
318-U1361A-015H-3-W-51a
1  saved in  lowrie__318-U1361A-015H-3-W-51a_.png
318-U1361A-015H-4-W-58a
1  saved in  lowrie__318-U1361A-015H-4-W-58a_.png
318-U1361A-015H-6-W-125a
1  saved in  lowrie__318-U1361A-015H-6-W-125a_.png
318-U1361A-016H-1-W-60a
1  saved in  lowrie__318-U1361A-016H-1-W-60a_.png
318-U1361A-016H-3-W-60a
1  saved in  lowrie__318-U1361A-016H-3-W-60a_.png
318-U1361A-016H-5-W-60a
1  saved in  lowrie__318-U1361A-016H-5-W-60a_.png
318-U1361A-017X-1-W-58a
1  saved in  lowrie__318-U1361A-017X-1-W-58a_.png
318-U1361A-017X-2-W-58a
1  saved in  lowrie__318-U1361A-017X-2-W-58a_.png
318-U1361A-017X-4-W-58a
1  saved in  lowrie__318-U1361A-017X-4-W-58a_.png
318-U1361A-017X-6-W-58a
1  saved in  lowrie__318-U1361A-017X-6-W-58a_.png
In [162]:
Image("lowrie__318-U1361A-008H-6-W-83a_.png")
Out[162]:
In [163]:
!lowrie_magic.py -f data_files/lowrie_magic/lowrie_magic_example.dat -fmt png -sav -DM 2
/Users/nebula/Python/PmagPy/data_files/lowrie_magic/lowrie_magic_example.dat
318-U1359A-002H-1-W-109
1  saved in  lowrie__318-U1359A-002H-1-W-109_.png
318-U1359A-002H-4-W-65
1  saved in  lowrie__318-U1359A-002H-4-W-65_.png
318-U1359A-002H-6-W-7
1  saved in  lowrie__318-U1359A-002H-6-W-7_.png
318-U1359A-003H-2-W-37
1  saved in  lowrie__318-U1359A-003H-2-W-37_.png
318-U1359A-003H-6-W-66
1  saved in  lowrie__318-U1359A-003H-6-W-66_.png
318-U1359A-004H-2-W-130
1  saved in  lowrie__318-U1359A-004H-2-W-130_.png
318-U1359A-004H-2-W-18
1  saved in  lowrie__318-U1359A-004H-2-W-18_.png
318-U1359A-004H-2-W-44
1  saved in  lowrie__318-U1359A-004H-2-W-44_.png
318-U1359A-004H-3-W-100
1  saved in  lowrie__318-U1359A-004H-3-W-100_.png
318-U1359A-004H-3-W-145
1  saved in  lowrie__318-U1359A-004H-3-W-145_.png
318-U1359A-004H-4-W-102
1  saved in  lowrie__318-U1359A-004H-4-W-102_.png
318-U1359A-004H-4-W-120
1  saved in  lowrie__318-U1359A-004H-4-W-120_.png
318-U1359A-004H-5-W-139
1  saved in  lowrie__318-U1359A-004H-5-W-139_.png
318-U1359A-006H-2-W-95
1  saved in  lowrie__318-U1359A-006H-2-W-95_.png
318-U1359A-006H-6-W-22
1  saved in  lowrie__318-U1359A-006H-6-W-22_.png
318-U1359A-007H-1-W-54
1  saved in  lowrie__318-U1359A-007H-1-W-54_.png
318-U1359A-007H-2-W-125
1  saved in  lowrie__318-U1359A-007H-2-W-125_.png
318-U1359A-007H-3-W-46
1  saved in  lowrie__318-U1359A-007H-3-W-46_.png
318-U1359A-009H-6-W-31
1  saved in  lowrie__318-U1359A-009H-6-W-31_.png
318-U1359A-010H-2-W-73
1  saved in  lowrie__318-U1359A-010H-2-W-73_.png
318-U1359A-010H-4-W-37
1  saved in  lowrie__318-U1359A-010H-4-W-37_.png
318-U1359A-010H-6-W-65
1  saved in  lowrie__318-U1359A-010H-6-W-65_.png
318-U1359A-011H-3-W-70
1  saved in  lowrie__318-U1359A-011H-3-W-70_.png
318-U1359A-012H-1-W-104
1  saved in  lowrie__318-U1359A-012H-1-W-104_.png
318-U1359A-012H-5-W-70
1  saved in  lowrie__318-U1359A-012H-5-W-70_.png
318-U1359A-013H-4-W-89
1  saved in  lowrie__318-U1359A-013H-4-W-89_.png
318-U1359A-013H-6-W-88
1  saved in  lowrie__318-U1359A-013H-6-W-88_.png
318-U1359A-014H-2-W-60
1  saved in  lowrie__318-U1359A-014H-2-W-60_.png
318-U1359A-014H-6-W-13
1  saved in  lowrie__318-U1359A-014H-6-W-13_.png
318-U1359A-015H-2-W-56
1  saved in  lowrie__318-U1359A-015H-2-W-56_.png
318-U1359A-015H-4-W-83
1  saved in  lowrie__318-U1359A-015H-4-W-83_.png
318-U1359A-018X-6-W-57
1  saved in  lowrie__318-U1359A-018X-6-W-57_.png
318-U1359A-022X-2-W-95
1  saved in  lowrie__318-U1359A-022X-2-W-95_.png
In [164]:
Image(filename='lowrie__318-U1359A-002H-1-W-109_.png')
Out[164]:

magic_select.py

[notebook version]

In [165]:
!magic_select.py -f data_files/magic_select/pmag_specimens.txt \
    -key magic_method_codes LP-DIR-AF has -F data_files/magic_select/AF_specimens.txt
76  records written to file  ./data_files/magic_select/AF_specimens.txt

mini_magic.py

[notebook version]

In [166]:
!mini_magic.py -WD data_files/convert_2_magic/mini_magic -f Peru_rev1.txt
33  records written to file  /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/measurements.txt
J-99-2-1
No data for dir_csd
J-99-2-1
No data for meas_n_orient
J-99-2-2
No data for dir_csd
J-99-2-2
No data for meas_n_orient
J-99-2-3
No data for dir_csd
J-99-2-3
No data for meas_n_orient
J-99-3-1
No data for dir_csd
J-99-3-1
No data for meas_n_orient
J-99-3-3
No data for dir_csd
J-99-3-3
No data for meas_n_orient
J-99-4-2
No data for dir_csd
J-99-4-2
No data for meas_n_orient
J-99-4-4
No data for dir_csd
J-99-4-4
No data for meas_n_orient
-I- Using online data model
-W- You are missing the 'treat_step_num' column in your measurements file
    This may cause strange behavior in the analysis GUIs
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 33 records written to measurements file
-I- writing specimens records to /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/specimens.txt
-I- 33 records written to specimens file
-I- writing samples records to /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/samples.txt
-I- 25 records written to samples file
-I- writing sites records to /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/sites.txt
-I- 7 records written to sites file
-I- writing locations records to /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/locations.txt
-I- 3 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/measurements.txt
-I- 33 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/specimens.txt
-I- 33 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/samples.txt
-I- 25 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/sites.txt
-I- 7 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/locations.txt
-I- 3 records written to locations file
results put in  /Users/nebula/Python/PmagPy/data_files/convert_2_magic/mini_magic/measurements.txt

mst_magic.py

[notebook version]

In [167]:
!mst_magic.py -f data_files/convert_2_magic/MsT_magic/curie_example.dat -spn specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
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no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
No site name found for:  specimen_name specimen_name
no location name for:  specimen_name
560  records written to file  /Users/nebula/Python/PmagPy/measurements.txt
results put in  /Users/nebula/Python/PmagPy/measurements.txt
-I- Using online data model
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 35 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 35 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
In [168]:
!mk_redo.py -WD data_files/mk_redo
Redo files saved to:  /Users/nebula/Python/PmagPy/data_files/mk_redo/zeq_redo /Users/nebula/Python/PmagPy/data_files/mk_redo/thellier_redo
In [169]:
!cat data_files/mk_redo/thellier_redo | head
sr01a1 573 823 
sr01a2 573 848 
sr01c2 673 823 
sr01d1 373 823 
sr01i1 373 773 
sr03a1 373 673 
sr03b1 373 673 
sr03c1 423 673 
sr03e1 423 673 
sr09f1 373 573 
In [170]:
!cat data_files/mk_redo/zeq_redo | head
sr01a1 DE-BFL 473 823 A 
sr01a2 DE-BFL 473 848 A 
sr01c2 DE-BFL 473 823 A 
sr01d1 DE-BFL 373 798 A 
sr01e2 DE-BFL 0.01 0.18 A 
sr01f2 DE-BFL 423 923 A 
sr01g2 DE-BFL 0.01 0.16 A 
sr01i1 DE-BFL 473 823 A 
sr03a1 DE-BFL 473 823 A 
sr03b1 DE-BFL 673 823 A 

orientation_magic.py

[notebook version]

In [171]:
try:
    os.remove('data_files/orientation_magic/samples.txt')
except FileNotFoundError:
    pass
!orientation_magic.py -WD data_files/orientation_magic -f orient_example.txt -gmt 13
!cat data_files/orientation_magic/samples.txt | head
Using default arguments for: -F, -A, -ID, -Fsa, -Fsi, -app, -ocn, -dcn, -BCN, -ncn, -mcd, -a, -DM
setting location name to ""
setting location name to ""
saving data...
24  records written to file  data_files/orientation_magic/samples.txt
2  records written to file  data_files/orientation_magic/sites.txt
Data saved in  data_files/orientation_magic/samples.txt  and  data_files/orientation_magic/sites.txt
tab 	samples
azimuth	azimuth_dec_correction	bed_dip	bed_dip_direction	citations	cooling_rate	cooling_rate_corr	cooling_rate_mcd	description	dip	geologic_classes	geologic_types	height	igsn	lat	lithologies	location	lon	method_codes	orientation_quality	sample	sample_alternatives	scientists	site	texture	timestamp
258.0		4	162.3	This study					-38.0					-78.25435		McMurdo	163.72913	SO-MAG		mc123a			mc123		2004:1:15:16:58
48.3	150.3	4	162.3	This study				Declination correction calculated from IGRF	-38.0					-78.25435		McMurdo	163.72913	SO-CMD-NORTH		mc123a			mc123		2004:1:15:16:58
35.8		4	162.3	This study					-38.0					-78.25435		McMurdo	163.72913	SO-SUN		mc123a			mc123		2004:1:15:16:58
242.0		4		This study					-30.0					-78.25435		McMurdo	163.72913	SO-MAG		mc123b			mc123		
32.3	150.3	4		This study				Declination correction calculated from IGRF	-30.0					-78.25435		McMurdo	163.72913	SO-CMD-NORTH		mc123b			mc123		
18.2		4		This study					-30.0					-78.25435		McMurdo	163.72913	SO-SUN		mc123b			mc123		
266.0		4		This study					-39.0					-78.25435		McMurdo	163.72913	SO-MAG		mc123c			mc123		
56.3	150.3	4		This study				Declination correction calculated from IGRF	-39.0					-78.25435		McMurdo	163.72913	SO-CMD-NORTH		mc123c			mc123		
In [172]:
!pca.py -dir L 1 10 -f data_files/pca/pca_example.txt
eba24a DE-BFL
0 0.00 339.9 57.9 9.2830e-05
1 2.50 325.7 49.1 7.5820e-05
2 5.00 321.3 45.9 6.2920e-05
3 10.00 314.8 41.7 5.2090e-05
4 15.00 310.3 38.7 4.4550e-05
5 20.00 305.0 37.0 3.9540e-05
6 30.00 303.9 34.7 3.2570e-05
7 40.00 303.0 32.3 2.5670e-05
8 50.00 303.6 32.4 2.2520e-05
9 60.00 299.8 30.8 1.9820e-05
10 70.00 292.5 31.0 1.3890e-05
11 80.00 297.0 25.6 1.2570e-05
12 90.00 299.3 11.3 0.5030e-05
eba24a DE-BFL 10    2.50  70.00    8.8   334.9    51.5

pmd_magic.py

[notebook version]

In [173]:
!pmd_magic.py -f data_files/convert_2_magic/PMD_magic/PMD/ss0207a.pmd
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 8 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 1 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 1 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 1 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 8 records written to measurements file

plotxy.py

In [174]:
!plotxy.py -f data_files/plotXY/plotXY_example.txt -fmt png -sav
Figure saved as  plotXY.png
In [175]:
Image(filename='plotXY.png')
Out[175]:
In [176]:
!plot_cdf.py -f data_files/plot_cdf/gaussian.out -fmt png -sav
1  saved in  CDF_.png
In [177]:
Image(filename='CDF_.png')
Out[177]:

plot_geomagia.py doesn't work on the command line - see _PmagPy_nb example.

plot_magmap.py

[notebook version]

In [178]:
!plot_magmap.py -el B -fmt png -sav
Figure saved as:  geomagnetic_field_2016.0.png
In [179]:
image = None
if cartopy_present:
    image = Image('geomagnetic_field_2016.0.png')
image
Out[179]:

plot_map_pts.py

[notebook version]

In [180]:
!plot_map_pts.py -f data_files/plot_map_pts/uniform.out -B -R \
    -prj ortho -eye 30 0 -etp -sym wo 10 -fmt png -sav
-W- plotting will require patience!
please wait to draw points
gridlines only supported for PlateCarree and Mercator plots currently
1  saved in  map_pts.png
In [181]:
image = None
if cartopy_present:
    image = Image(filename='map_pts.png')
image
Out[181]:
In [182]:
!plotdi_a.py -f data_files/plotdi_a/plotdi_a_example.dat -fmt png -sav
1  saved in  eq.png
In [183]:
Image(filename='eq.png')
Out[183]:

pmag_results_extract.py

In [184]:
!pmag_results_extract.py -WD data_files/pmag_results_extract -f pmag_results.txt
data saved in:  /Users/nebula/Python/PmagPy/data_files/pmag_results_extract/Directions.txt /Users/nebula/Python/PmagPy/data_files/pmag_results_extract/Intensities.txt /Users/nebula/Python/PmagPy/data_files/pmag_results_extract/SiteNfo.txt

polemap_magic.py

[notebook version]

In [185]:
!polemap_magic.py -WD data_files/polemap_magic -sav -fmt png
-I- Using online data model
gridlines only supported for PlateCarree and Mercator plots currently
1  saved in  Skaistgirys Carbonates_Cismon Section_Monte Raparo_POLE_map.png
In [186]:
image = None
if cartopy_present:
    image = Image(filename="Skaistgirys Carbonates_Cismon Section_Monte Raparo_POLE_map.png")
image
Out[186]:
In [187]:
!awk '{print $1,$2}' data_files/pt_rot/pt_rot.input > data_files/pt_rot/lon_lat
!plot_map_pts.py -prj moll -f data_files/pt_rot/lon_lat -sym g^ 10 -R -B -eye 0 0 -fmt png -sav
please wait to draw points
gridlines only supported for PlateCarree and Mercator plots currently
1  saved in  map_pts.png
In [188]:
image
if cartopy_present:
    image = Image(filename='map_pts.png')

image
Out[188]:
In [189]:
!cat data_files/pt_rot/pt_rot.input
!pt_rot.py -f data_files/pt_rot/pt_rot.input > data_files/pt_rot/pt_rot.out
-84.7 39.1 nam 80 saf
In [190]:
!plot_map_pts.py -prj moll -f data_files/pt_rot/pt_rot.out -sym ro 10 -R -B -eye 0 0 -fmt png -sav
please wait to draw points
gridlines only supported for PlateCarree and Mercator plots currently
1  saved in  map_pts.png
In [191]:
if cartopy_present:
    image = Image(filename='map_pts.png')
image
Out[191]:

Something still weird about pt_rot.py (the -ff option).

In [192]:
!pt_rot.py -ff data_files/pt_rot/nam_180-200.txt data_files/pt_rot/nam_panA.frp > data_files/pt_rot/pt_rot_panA.out
In [193]:
!plot_map_pts.py -f data_files/pt_rot/pt_rot_panA.out -prj ortho -eye 60 90 -sym ro 10 -B -R -fmt png -sav
please wait to draw points
gridlines only supported for PlateCarree and Mercator plots currently
1  saved in  map_pts.png
In [194]:
image = None
if cartopy_present:
    image = Image(filename='Map_pts.png')
image
Out[194]:
In [195]:
!qqplot.py -f data_files/qqplot/gauss.out -fmt png -sav
1  saved in  qq.png
In [196]:
Image(filename='qq.png')
Out[196]:

quick_hyst.py

In [197]:
!quick_hyst.py -WD data_files/3_0/McMurdo -spc mc04c-1 -fmt png

Image("McMurdo_mc04c_mc04c_mc04c-1_hyst.png")
-I- Using online data model
['mc04c-1' 'mc113a1-1' 'mc117a2-1' 'mc120a2-1' 'mc129a1-1' 'mc164a2-1'
 'mc205a1-1' 'mc217a2-1']
working on t:  273
1  saved in  McMurdo_mc04c_mc04c_mc04c-1_hyst.png
Out[197]:

quick_hyst2.py

In [198]:
!quick_hyst2.py -f data_files/hysteresis_magic/hysteresis_magic_example.dat -fmt png -sav
verbose 0
working on t:  273
1  saved in  IS06_IS06a_IS06a-1_hyst.png
working on t:  273
1  saved in  IS06_IS06a_IS06a-2_hyst.png
working on t:  273
1  saved in  IS06_IS06a_IS06a-3_hyst.png
working on t:  273
1  saved in  IS06_IS06a_IS06a-4_hyst.png
working on t:  273
1  saved in  IS06_IS06a_IS06a-5_hyst.png
working on t:  273
1  saved in  IS06_IS06a_IS06a-6_hyst.png
working on t:  273
1  saved in  IS06_IS06a_IS06a-8_hyst.png
working on t:  273
1  saved in  IS06_IS06a_IS06a-9_hyst.png
In [199]:
Image(filename='IS06_IS06a_IS06a-1_hyst.png')
Out[199]:
In [200]:
!revtest.py -f data_files/revtest/revtest_example.txt -fmt png -sav
doing first mode, be patient
doing second mode, be patient
1  saved in  REV_X.png
2  saved in  REV_Y.png
3  saved in  REV_Z.png
In [201]:
Image(filename='REV_X.png')
Out[201]:
In [202]:
Image(filename='REV_Y.png')
Out[202]:
In [203]:
Image(filename='REV_Z.png')
Out[203]:

revtest_magic.py

[notebook version]

In [204]:
!revtest_magic.py -f data_files/revtest_magic/sites.txt -fmt png -sav -DM 3 -exc
doing first mode, be patient
doing second mode, be patient
1  saved in  REV_X.png
2  saved in  REV_Y.png
3  saved in  REV_Z.png
In [205]:
Image("Rev_Y.png")
Out[205]:
In [206]:
!revtest_magic.py -f data_files/revtest_magic/revtest_magic_example.txt -fmt png -sav -DM 2
doing first mode, be patient
doing second mode, be patient
1  saved in  REV_X.png
2  saved in  REV_Y.png
3  saved in  REV_Z.png
In [207]:
Image(filename='REV_X.png')
Out[207]:
In [208]:
!s_eigs.py -f data_files/s_eigs/s_eigs_example.dat
0.33127186 239.53  44.70 0.33351338 126.62  21.47 0.33521473  19.03  37.54
0.33177859 281.12   6.18 0.33218277 169.79  73.43 0.33603862  12.82  15.32
0.33046979 283.57  27.30 0.33328307 118.37  61.91 0.33624712  16.75   6.13
0.33123776 261.36  12.07 0.33377582 141.40  66.82 0.33498645 355.70  19.48
0.33085680 255.71   7.13 0.33379164 130.85  77.65 0.33535156 346.97  10.03
0.33175930 268.51  26.79 0.33405024 169.66  16.95 0.33419049  51.04  57.53
0.33194992 261.59  20.68 0.33313262  92.18  68.99 0.33491743 352.93   3.54
0.33157593 281.42  21.32 0.33312121 117.04  67.94 0.33530283  13.54   5.41
In [209]:
!s_geo.py -f data_files/s_geo/s_geo_example.dat
0.33412680 0.33282733 0.33304587 -0.00015289 0.00124843 0.00135721 
0.33556300 0.33198264 0.33245432 0.00087259 0.00024141 0.00096166 
0.33584908 0.33140627 0.33274469 0.00131845 0.00118816 0.00002986 
0.33479756 0.33142531 0.33377719 -0.00047493 0.00049539 0.00044303 
0.33505613 0.33114848 0.33379540 -0.00101375 0.00028536 0.00034852 
0.33406156 0.33226916 0.33366925 -0.00002267 0.00098548 0.00005553 
0.33486596 0.33216032 0.33297369 -0.00035492 0.00039254 0.00015403 
0.33510646 0.33196402 0.33292958 0.00075965 0.00057242 0.00010112 
In [210]:
!s_geo.py -f data_files/s_geo/s_geo_example.dat | s_hext.py
F =  5.79 F12 =  3.55 F23 =  3.66
N =  8  sigma =  0.000641809950
0.33505     5.3    14.7    25.5   124.5    61.7    13.3   268.8    23.6
0.33334   124.5    61.7    25.1   268.8    23.6    25.5     5.3    14.7
0.33161   268.8    23.6    13.3     5.3    14.7    25.1   124.5    61.7

sio_magic.py

[notebook version]

In [211]:
!s_tilt.py -f data_files/s_tilt/s_tilt_example.dat
0.33455709 0.33192658 0.33351630 -0.00043562 0.00092779 0.00105006 
0.33585501 0.33191565 0.33222935 0.00055960 -0.00005316 0.00064732 
0.33586669 0.33084923 0.33328408 0.00142266 0.00013234 0.00009203 
0.33488664 0.33138493 0.33372843 -0.00056597 -0.00039085 0.00004873 
0.33506602 0.33127019 0.33366373 -0.00105193 -0.00057257 -0.00029959 
0.33407688 0.33177567 0.33414748 0.00007007 0.00018447 0.00005073 
0.33483925 0.33197853 0.33318222 -0.00028447 0.00003518 -0.00029262 
0.33513144 0.33175036 0.33311823 0.00077914 -0.00006402 0.00004612 
In [212]:
!s_magic.py -WD data_files/convert_2_magic/s_magic -f s_magic_example.dat 
8  records written to file  /Users/nebula/Python/PmagPy/data_files/convert_2_magic/s_magic/specimens.txt
data saved in  /Users/nebula/Python/PmagPy/data_files/convert_2_magic/s_magic/specimens.txt
-I- Using online data model
-I- Creating new samples table with data from specimens table
-I- writing samples records to /Users/nebula/Python/PmagPy/data_files/convert_2_magic/s_magic/samples.txt
-I- 8 records written to samples file
-I- Creating new sites table with data from samples table
-I- writing sites records to /Users/nebula/Python/PmagPy/data_files/convert_2_magic/s_magic/sites.txt
-I- 1 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/data_files/convert_2_magic/s_magic/samples.txt
-I- 8 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/data_files/convert_2_magic/s_magic/sites.txt
-I- 1 records written to sites file
In [213]:
!scalc.py -f data_files/scalc/scalc_example.txt
100    21.8    180.0 
In [214]:
!scalc.py < data_files/scalc/scalc_example.txt
100    21.8    180.0 
In [215]:
!scalc.py -f data_files/scalc/scalc_example.txt -v
89    15.2     32.3 
In [216]:
!scalc.py -f data_files/scalc/scalc_example.txt -v -b
89    15.2    13.3     16.8    32.3 

scalc_magic.py

[notebook version]

In [217]:
!scalc_magic.py -f data_files/scalc_magic/sites.txt -c 30
13    17.9     30.0 
In [218]:
!scalc_magic.py -f data_files/scalc_magic/pmag_results.txt -c 30 -dm 2
13    17.9     30.0 

site_edit.py

This program requires user interaction and can only be used on the command line.

specimens_results_magic.py

This program has been superceded by Pmag GUI and is not maintained.

In [219]:
!stats.py -f data_files/gaussian/gauss.out
100 9.94986999 994.9869990000003 0.9581673609207783 9.629948550923512

strip_magic.py

[notebook version]

In [220]:
!strip_magic.py -f data_files/strip_magic/pmag_results.txt -x age -y lat -fmt png -sav -DM 2
1  saved in  strat.png
In [221]:
Image(filename='strat.png')
Out[221]:
In [222]:
!rm strat.png
!strip_magic.py -f data_files/strip_magic/sites_with_vgps.txt -x age -y lat -fmt png -sav -DM 3
1  saved in  strat.png
In [223]:
Image(filename='strat.png')
Out[223]:
In [224]:
!sundec.py -f data_files/sundec/sundec_example.dat
  154.2

thellier_magic.py

[notebook version]

This program is no longer maintained - try Thellier GUI instead.

thellier_magic_redo.py

The function of this program has been incorporated into Thellier GUI so you should use that instead.

In [225]:
!tk03.py -lat 30 > data_files/tk03/tk03.out
!eqarea.py -f data_files/tk03/tk03.out -fmt png -sav
1  saved in  tk03_eq.png
In [226]:
Image(filename='tk03_eq.png')
Out[226]:

trmaq_magic.py

[notebook version]

In [227]:
!trmaq_magic.py -ft data_files/3_0/McMurdo/specimens.txt \
    -f data_files/3_0/McMurdo/measurements.txt -sav -fmt png
mc01a 1 of  1046 Best =  13.5
skipping specimen -  no trm acquisition data  mc01a
mc01b 2 of  1046 Best =  13.9
skipping specimen -  no trm acquisition data  mc01b
skipping  mc01c  : no best 
mc01d 4 of  1046 Best =  18.7
skipping specimen -  no trm acquisition data  mc01d
skipping  mc01e  : no best 
skipping  mc01f  : no best 
mc01g 7 of  1046 Best =  20.1
skipping specimen -  no trm acquisition data  mc01g
skipping  mc01h  : no best 
skipping  mc02a  : no best 
skipping  mc02b  : no best 
skipping  mc02c  : no best 
skipping  mc02e  : no best 
mc02f 13 of  1046 Best =  16.7
skipping specimen -  no trm acquisition data  mc02f
skipping  mc02g  : no best 
skipping  mc02h  : no best 
skipping  mc03a  : no best 
skipping  mc03b  : no best 
skipping  mc03c  : no best 
skipping  mc03d  : no best 
skipping  mc03f  : no best 
skipping  mc03h  : no best 
skipping  mc04a  : no best 
skipping  mc04b  : no best 
skipping  mc04c-1  : no best 
skipping  mc04e  : no best 
skipping  mc04f  : no best 
skipping  mc04g  : no best 
skipping  mc04h  : no best 
skipping  mc06a  : no best 
skipping  mc06c  : no best 
skipping  mc06d  : no best 
skipping  mc06g  : no best 
mc06h 33 of  1046 Best =  27.7
skipping specimen -  no trm acquisition data  mc06h
skipping  mc07b  : no best 
skipping  mc07c  : no best 
skipping  mc07d  : no best 
skipping  mc07e  : no best 
skipping  mc07f  : no best 
mc08a 39 of  1046 Best =  44.9
skipping specimen -  no trm acquisition data  mc08a
mc08b 40 of  1046 Best =  41.9
skipping specimen -  no trm acquisition data  mc08b
skipping  mc08c  : no best 
skipping  mc08d  : no best 
skipping  mc08e  : no best 
skipping  mc08f  : no best 
mc08g 45 of  1046 Best =  43.300000000000004
skipping specimen -  no trm acquisition data  mc08g
mc08h 46 of  1046 Best =  44.0
skipping specimen -  no trm acquisition data  mc08h
mc09a 47 of  1046 Best =  27.1
skipping specimen -  no trm acquisition data  mc09a
mc09b 48 of  1046 Best =  26.1
skipping specimen -  no trm acquisition data  mc09b
skipping  mc09c  : no best 
mc09d 50 of  1046 Best =  28.099999999999998
skipping specimen -  no trm acquisition data  mc09d
skipping  mc09e  : no best 
skipping  mc09f  : no best 
skipping  mc09g  : no best 
skipping  mc09h  : no best 
skipping  mc100a1  : no best 
skipping  mc100d1  : no best 
skipping  mc100e1  : no best 
skipping  mc100e2  : no best 
skipping  mc100f2  : no best 
skipping  mc100g1  : no best 
skipping  mc100g2  : no best 
skipping  mc100h2  : no best 
skipping  mc101a1  : no best 
skipping  mc101b1  : no best 
skipping  mc101c1  : no best 
skipping  mc101d1  : no best 
skipping  mc101f1  : no best 
skipping  mc101h1  : no best 
skipping  mc102a1  : no best 
skipping  mc102a2  : no best 
skipping  mc102b1  : no best 
skipping  mc102b2  : no best 
skipping  mc102e1  : no best 
skipping  mc102f1  : no best 
skipping  mc102g1  : no best 
skipping  mc102m2  : no best 
skipping  mc103a1  : no best 
skipping  mc103a2  : no best 
skipping  mc103b1  : no best 
skipping  mc103b2  : no best 
skipping  mc103c1  : no best 
skipping  mc103c2  : no best 
skipping  mc103d1  : no best 
skipping  mc103d2  : no best 
mc103e1 85 of  1046 Best =  21.0
skipping specimen -  no trm acquisition data  mc103e1
skipping  mc103e2  : no best 
skipping  mc104a1  : no best 
skipping  mc104b1  : no best 
skipping  mc104b2  : no best 
skipping  mc104c1  : no best 
skipping  mc104c2  : no best 
skipping  mc104d1  : no best 
skipping  mc104f1  : no best 
skipping  mc105a1  : no best 
mc105a2 95 of  1046 Best =  27.1
skipping specimen -  no trm acquisition data  mc105a2
mc105c1 96 of  1046 Best =  28.4
skipping specimen -  no trm acquisition data  mc105c1
mc105d1 97 of  1046 Best =  27.6
skipping specimen -  no trm acquisition data  mc105d1
skipping  mc105f1  : no best 
skipping  mc105g1  : no best 
skipping  mc105h1  : no best 
mc105j1 101 of  1046 Best =  31.4
skipping specimen -  no trm acquisition data  mc105j1
skipping  mc106a1  : no best 
skipping  mc106b1  : no best 
skipping  mc106c1  : no best 
skipping  mc106d1  : no best 
skipping  mc106e1  : no best 
skipping  mc107c1  : no best 
skipping  mc107d2  : no best 
skipping  mc107e1  : no best 
mc107e2 110 of  1046 Best =  15.2
skipping specimen -  no trm acquisition data  mc107e2
skipping  mc107h1  : no best 
skipping  mc107k1  : no best 
skipping  mc107l1  : no best 
skipping  mc108a1  : no best 
skipping  mc108a2  : no best 
skipping  mc108b1  : no best 
skipping  mc108c1  : no best 
skipping  mc108d1  : no best 
skipping  mc108g2  : no best 
skipping  mc108h1  : no best 
skipping  mc108k1  : no best 
mc109a1 122 of  1046 Best =  36.0
skipping specimen -  no trm acquisition data  mc109a1
skipping  mc109a2  : no best 
mc109c1 124 of  1046 Best =  34.8
skipping specimen -  no trm acquisition data  mc109c1
mc109d1 125 of  1046 Best =  33.699999999999996
skipping specimen -  no trm acquisition data  mc109d1
mc109e1 126 of  1046 Best =  30.3
skipping specimen -  no trm acquisition data  mc109e1
skipping  mc109i1  : no best 
mc10a 128 of  1046 Best =  29.5
skipping specimen -  no trm acquisition data  mc10a
mc10b 129 of  1046 Best =  29.7
skipping specimen -  no trm acquisition data  mc10b
skipping  mc10c  : no best 
mc10d 131 of  1046 Best =  37.4
skipping specimen -  no trm acquisition data  mc10d
skipping  mc10e  : no best 
skipping  mc10f  : no best 
skipping  mc10g  : no best 
skipping  mc10h  : no best 
skipping  mc110a1  : no best 
skipping  mc110a2  : no best 
skipping  mc110b1  : no best 
skipping  mc110b2  : no best 
skipping  mc110d1  : no best 
skipping  mc110g1  : no best 
skipping  mc110i1  : no best 
skipping  mc111a2  : no best 
skipping  mc111b1  : no best 
skipping  mc111d1  : no best 
mc111d2 146 of  1046 Best =  27.6
skipping specimen -  no trm acquisition data  mc111d2
skipping  mc111e1  : no best 
mc111e2 148 of  1046 Best =  28.2
skipping specimen -  no trm acquisition data  mc111e2
skipping  mc111f1  : no best 
skipping  mc111l1  : no best 
skipping  mc112a1  : no best 
skipping  mc112b2  : no best 
skipping  mc112c1  : no best 
skipping  mc112c2  : no best 
skipping  mc112d1  : no best 
skipping  mc112g1  : no best 
skipping  mc112h3  : no best 
skipping  mc112j1  : no best 
skipping  mc113a1  : no best 
skipping  mc113a1-1  : no best 
mc113a2 161 of  1046 Best =  11.0
skipping specimen -  no trm acquisition data  mc113a2
skipping  mc113b1  : no best 
skipping  mc113c1  : no best 
skipping  mc113e1  : no best 
skipping  mc113f1  : no best 
skipping  mc113g1  : no best 
skipping  mc113h1  : no best 
mc113j1 168 of  1046 Best =  11.5
skipping specimen -  no trm acquisition data  mc113j1
mc113m1 169 of  1046 Best =  12.1
skipping specimen -  no trm acquisition data  mc113m1
skipping  mc114a1  : no best 
skipping  mc114b2  : no best 
skipping  mc114c1  : no best 
skipping  mc114d2  : no best 
skipping  mc114e1  : no best 
skipping  mc114i1  : no best 
skipping  mc115a1  : no best 
mc115a2 177 of  1046 Best =  24.9
skipping specimen -  no trm acquisition data  mc115a2
mc115b1 178 of  1046 Best =  24.3
skipping specimen -  no trm acquisition data  mc115b1
mc115e1 179 of  1046 Best =  24.7
skipping specimen -  no trm acquisition data  mc115e1
skipping  mc115g2  : no best 
skipping  mc115h1  : no best 
skipping  mc116a1  : no best 
mc116b1 183 of  1046 Best =  38.5
skipping specimen -  no trm acquisition data  mc116b1
skipping  mc116c1  : no best 
skipping  mc116i2  : no best 
mc116j2 186 of  1046 Best =  41.0
skipping specimen -  no trm acquisition data  mc116j2
mc117a1 187 of  1046 Best =  25.5
skipping specimen -  no trm acquisition data  mc117a1
skipping  mc117a2  : no best 
skipping  mc117a2-1  : no best 
mc117b1 190 of  1046 Best =  26.2
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 111
         Function evaluations: 209
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 49
         Function evaluations: 92
Banc=  26.214351298075737
1  saved in  mc117b1_TRM.png
mc117d2 191 of  1046 Best =  26.8
skipping specimen -  no trm acquisition data  mc117d2
mc117e2 192 of  1046 Best =  27.2
skipping specimen -  no trm acquisition data  mc117e2
skipping  mc117h1  : no best 
skipping  mc118a1  : no best 
skipping  mc118c1  : no best 
skipping  mc118d1  : no best 
skipping  mc118e1  : no best 
skipping  mc118f1  : no best 
skipping  mc118i1  : no best 
skipping  mc118l2  : no best 
mc119a1 201 of  1046 Best =  42.4
skipping specimen -  no trm acquisition data  mc119a1
mc119b1 202 of  1046 Best =  43.6
skipping specimen -  no trm acquisition data  mc119b1
skipping  mc119b2  : no best 
mc119d2 204 of  1046 Best =  39.1
skipping specimen -  no trm acquisition data  mc119d2
mc119e2 205 of  1046 Best =  40.3
skipping specimen -  no trm acquisition data  mc119e2
mc119f2 206 of  1046 Best =  39.5
skipping specimen -  no trm acquisition data  mc119f2
skipping  mc11a  : no best 
mc11b 208 of  1046 Best =  48.099999999999994
skipping specimen -  no trm acquisition data  mc11b
mc11c 209 of  1046 Best =  51.400000000000006
skipping specimen -  no trm acquisition data  mc11c
skipping  mc11d  : no best 
mc11e 211 of  1046 Best =  30.3
skipping specimen -  no trm acquisition data  mc11e
skipping  mc11f  : no best 
skipping  mc11g  : no best 
mc11h 214 of  1046 Best =  22.799999999999997
skipping specimen -  no trm acquisition data  mc11h
mc120a1 215 of  1046 Best =  24.7
skipping specimen -  no trm acquisition data  mc120a1
skipping  mc120a2  : no best 
skipping  mc120a2-1  : no best 
mc120b1 218 of  1046 Best =  24.7
skipping specimen -  no trm acquisition data  mc120b1
mc120b2 219 of  1046 Best =  25.0
skipping specimen -  no trm acquisition data  mc120b2
mc120c1 220 of  1046 Best =  23.900000000000002
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 121
         Function evaluations: 227
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 46
         Function evaluations: 90
Banc=  23.888891833665905
1  saved in  mc120c1_TRM.png
mc120f1 221 of  1046 Best =  23.200000000000003
skipping specimen -  no trm acquisition data  mc120f1
skipping  mc120j2  : no best 
skipping  mc120l1  : no best 
skipping  mc120m2  : no best 
skipping  mc121a1  : no best 
mc121c1 226 of  1046 Best =  12.0
skipping specimen -  no trm acquisition data  mc121c1
skipping  mc121c3  : no best 
mc121d1 228 of  1046 Best =  24.0
skipping specimen -  no trm acquisition data  mc121d1
skipping  mc121d2  : no best 
mc121e1 230 of  1046 Best =  28.2
skipping specimen -  no trm acquisition data  mc121e1
skipping  mc121e2  : no best 
mc121f2 232 of  1046 Best =  20.5
skipping specimen -  no trm acquisition data  mc121f2
mc121g1 233 of  1046 Best =  34.7
skipping specimen -  no trm acquisition data  mc121g1
skipping  mc121i1  : no best 
mc121k1 235 of  1046 Best =  27.5
skipping specimen -  no trm acquisition data  mc121k1
mc121k2 236 of  1046 Best =  25.8
skipping specimen -  no trm acquisition data  mc121k2
skipping  mc122a1  : no best 
skipping  mc122b1  : no best 
skipping  mc122c1  : no best 
skipping  mc122d1  : no best 
skipping  mc122f1  : no best 
skipping  mc122g1  : no best 
skipping  mc122k2  : no best 
skipping  mc122l1  : no best 
skipping  mc123a1  : no best 
mc123a2 246 of  1046 Best =  33.0
skipping specimen -  no trm acquisition data  mc123a2
mc123b1 247 of  1046 Best =  27.6
skipping specimen -  no trm acquisition data  mc123b1
mc123b2 248 of  1046 Best =  30.2
skipping specimen -  no trm acquisition data  mc123b2
skipping  mc123c2  : no best 
mc123c3 250 of  1046 Best =  29.3
skipping specimen -  no trm acquisition data  mc123c3
skipping  mc123f1  : no best 
skipping  mc123j1  : no best 
mc124a1 253 of  1046 Best =  23.6
skipping specimen -  no trm acquisition data  mc124a1
skipping  mc124d1  : no best 
mc124d2 255 of  1046 Best =  19.3
skipping specimen -  no trm acquisition data  mc124d2
skipping  mc124f1  : no best 
skipping  mc124g1  : no best 
skipping  mc124h1  : no best 
skipping  mc124j1  : no best 
skipping  mc124l1  : no best 
skipping  mc125a1  : no best 
skipping  mc125b1  : no best 
skipping  mc125c1  : no best 
mc125d1 264 of  1046 Best =  6.07
skipping specimen -  no trm acquisition data  mc125d1
mc125e1 265 of  1046 Best =  5.14
skipping specimen -  no trm acquisition data  mc125e1
skipping  mc125e3  : no best 
skipping  mc125g1  : no best 
mc125i1 268 of  1046 Best =  25.9
skipping specimen -  no trm acquisition data  mc125i1
skipping  mc125m1  : no best 
skipping  mc126a2  : no best 
skipping  mc126c1  : no best 
skipping  mc126c2  : no best 
skipping  mc126d1  : no best 
skipping  mc126e1  : no best 
skipping  mc126f1  : no best 
skipping  mc126g1  : no best 
skipping  mc126i1  : no best 
skipping  mc127a1  : no best 
mc127a2 279 of  1046 Best =  39.6
skipping specimen -  no trm acquisition data  mc127a2
skipping  mc127b1  : no best 
mc127c1 281 of  1046 Best =  37.4
skipping specimen -  no trm acquisition data  mc127c1
mc127d1 282 of  1046 Best =  36.5
skipping specimen -  no trm acquisition data  mc127d1
skipping  mc127f1  : no best 
skipping  mc127g2  : no best 
skipping  mc127i1  : no best 
skipping  mc128b1  : no best 
mc128b2 287 of  1046 Best =  32.7
skipping specimen -  no trm acquisition data  mc128b2
mc128c2 288 of  1046 Best =  37.4
skipping specimen -  no trm acquisition data  mc128c2
skipping  mc128d1  : no best 
skipping  mc128e1  : no best 
skipping  mc128e2  : no best 
skipping  mc128f1  : no best 
skipping  mc128h1  : no best 
mc128j1 294 of  1046 Best =  32.8
skipping specimen -  no trm acquisition data  mc128j1
skipping  mc129a1  : no best 
skipping  mc129a1-1  : no best 
skipping  mc129a2  : no best 
mc129b1 298 of  1046 Best =  49.9
skipping specimen -  no trm acquisition data  mc129b1
mc129c1 299 of  1046 Best =  49.0
skipping specimen -  no trm acquisition data  mc129c1
skipping  mc129c2  : no best 
skipping  mc129f1  : no best 
skipping  mc129h2  : no best 
skipping  mc129j1  : no best 
mc129l1 304 of  1046 Best =  18.099999999999998
skipping specimen -  no trm acquisition data  mc129l1
mc130a1 305 of  1046 Best =  29.3
skipping specimen -  no trm acquisition data  mc130a1
skipping  mc130a2  : no best 
skipping  mc130b1  : no best 
mc130d1 308 of  1046 Best =  21.1
skipping specimen -  no trm acquisition data  mc130d1
skipping  mc130e1  : no best 
skipping  mc130g2  : no best 
mc130h1 311 of  1046 Best =  17.200000000000003
skipping specimen -  no trm acquisition data  mc130h1
skipping  mc130i2  : no best 
skipping  mc130j2  : no best 
skipping  mc131a3  : no best 
mc131b1 315 of  1046 Best =  16.099999999999998
skipping specimen -  no trm acquisition data  mc131b1
mc131c2 316 of  1046 Best =  16.799999999999997
skipping specimen -  no trm acquisition data  mc131c2
mc131d2 317 of  1046 Best =  16.2
skipping specimen -  no trm acquisition data  mc131d2
mc131e1 318 of  1046 Best =  16.5
skipping specimen -  no trm acquisition data  mc131e1
skipping  mc131f1  : no best 
mc131g1 320 of  1046 Best =  18.3
skipping specimen -  no trm acquisition data  mc131g1
skipping  mc131k1  : no best 
skipping  mc132a1  : no best 
skipping  mc132c1  : no best 
skipping  mc132d1  : no best 
skipping  mc132e1  : no best 
mc132e2 326 of  1046 Best =  3.46
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 96
         Function evaluations: 182
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 49
         Function evaluations: 92
Banc=  3.421376846090002
1  saved in  mc132e2_TRM.png
mc132f2 327 of  1046 Best =  3.27
skipping specimen -  no trm acquisition data  mc132f2
mc132g2 328 of  1046 Best =  3.28
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 93
         Function evaluations: 174
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 48
         Function evaluations: 91
Banc=  3.252676110475162
1  saved in  mc132g2_TRM.png
mc132h2 329 of  1046 Best =  3.1599999999999997
skipping specimen -  no trm acquisition data  mc132h2
mc132i2 330 of  1046 Best =  3.45
skipping specimen -  no trm acquisition data  mc132i2
mc132j1 331 of  1046 Best =  3.07
skipping specimen -  no trm acquisition data  mc132j1
skipping  mc132j2  : no best 
mc132k1 333 of  1046 Best =  3.36
skipping specimen -  no trm acquisition data  mc132k1
skipping  mc132l1  : no best 
skipping  mc133b2  : no best 
skipping  mc133d1  : no best 
mc133f1 337 of  1046 Best =  43.900000000000006
skipping specimen -  no trm acquisition data  mc133f1
skipping  mc133f2  : no best 
mc133g1 339 of  1046 Best =  48.699999999999996
skipping specimen -  no trm acquisition data  mc133g1
skipping  mc133h1  : no best 
skipping  mc133j1  : no best 
mc133l1 342 of  1046 Best =  47.3
skipping specimen -  no trm acquisition data  mc133l1
skipping  mc134a1  : no best 
skipping  mc134c1  : no best 
mc134c2 345 of  1046 Best =  18.6
skipping specimen -  no trm acquisition data  mc134c2
skipping  mc134e1  : no best 
mc134f1 347 of  1046 Best =  2.1900000000000004
skipping specimen -  no trm acquisition data  mc134f1
skipping  mc134k1  : no best 
mc135a1 349 of  1046 Best =  35.5
skipping specimen -  no trm acquisition data  mc135a1
skipping  mc135b1  : no best 
mc135c2 351 of  1046 Best =  41.1
skipping specimen -  no trm acquisition data  mc135c2
skipping  mc135d2  : no best 
mc135e1 353 of  1046 Best =  11.5
skipping specimen -  no trm acquisition data  mc135e1
skipping  mc135e2  : no best 
skipping  mc135h2  : no best 
skipping  mc135i2  : no best 
skipping  mc136a1  : no best 
mc136a2 358 of  1046 Best =  1.42
skipping specimen -  no trm acquisition data  mc136a2
skipping  mc136c1  : no best 
skipping  mc136d1  : no best 
skipping  mc136d2  : no best 
skipping  mc136e1  : no best 
skipping  mc136g1  : no best 
skipping  mc136h2  : no best 
skipping  mc136i1  : no best 
skipping  mc136i2  : no best 
skipping  mc137a1  : no best 
skipping  mc137d1  : no best 
skipping  mc137h1  : no best 
skipping  mc137j2  : no best 
skipping  mc137l1  : no best 
skipping  mc138a1  : no best 
skipping  mc138b1  : no best 
skipping  mc138d1  : no best 
skipping  mc138g1  : no best 
skipping  mc138h1  : no best 
mc139a1 377 of  1046 Best =  5.36
skipping specimen -  no trm acquisition data  mc139a1
skipping  mc139a2  : no best 
mc139c1 379 of  1046 Best =  19.8
skipping specimen -  no trm acquisition data  mc139c1
skipping  mc139d1  : no best 
skipping  mc139e1  : no best 
skipping  mc139h1  : no best 
skipping  mc139j2  : no best 
mc13a 384 of  1046 Best =  28.5
skipping specimen -  no trm acquisition data  mc13a
mc13b 385 of  1046 Best =  30.0
skipping specimen -  no trm acquisition data  mc13b
mc13c 386 of  1046 Best =  32.8
skipping specimen -  no trm acquisition data  mc13c
mc13d 387 of  1046 Best =  31.6
skipping specimen -  no trm acquisition data  mc13d
skipping  mc13e  : no best 
skipping  mc13f  : no best 
skipping  mc13g  : no best 
skipping  mc13h  : no best 
mc140a1 392 of  1046 Best =  19.1
skipping specimen -  no trm acquisition data  mc140a1
mc140b1 393 of  1046 Best =  13.7
skipping specimen -  no trm acquisition data  mc140b1
mc140c1 394 of  1046 Best =  17.200000000000003
skipping specimen -  no trm acquisition data  mc140c1
mc140d1 395 of  1046 Best =  19.700000000000003
skipping specimen -  no trm acquisition data  mc140d1
skipping  mc140e1  : no best 
skipping  mc140g1  : no best 
skipping  mc140h1  : no best 
skipping  mc140j1  : no best 
skipping  mc141b1  : no best 
skipping  mc141b2  : no best 
skipping  mc141c1  : no best 
skipping  mc141g1  : no best 
skipping  mc141h3  : no best 
skipping  mc141k2  : no best 
skipping  mc141l1  : no best 
skipping  mc142b2  : no best 
mc142c1 408 of  1046 Best =  14.8
skipping specimen -  no trm acquisition data  mc142c1
skipping  mc142c2  : no best 
mc142d1 410 of  1046 Best =  13.4
skipping specimen -  no trm acquisition data  mc142d1
skipping  mc142e1  : no best 
mc142e2 412 of  1046 Best =  14.3
skipping specimen -  no trm acquisition data  mc142e2
mc142f2 413 of  1046 Best =  14.2
skipping specimen -  no trm acquisition data  mc142f2
skipping  mc142i2  : no best 
skipping  mc142k1  : no best 
mc142k2 416 of  1046 Best =  18.7
skipping specimen -  no trm acquisition data  mc142k2
skipping  mc143a1  : no best 
skipping  mc143b1  : no best 
skipping  mc143c1  : no best 
skipping  mc143d2  : no best 
skipping  mc143g1  : no best 
skipping  mc143h1  : no best 
skipping  mc143i1  : no best 
skipping  mc144a1  : no best 
skipping  mc144b1  : no best 
skipping  mc144d1  : no best 
mc144e1 427 of  1046 Best =  19.700000000000003
skipping specimen -  no trm acquisition data  mc144e1
mc144f1 428 of  1046 Best =  18.2
skipping specimen -  no trm acquisition data  mc144f1
mc144h1 429 of  1046 Best =  6.66
skipping specimen -  no trm acquisition data  mc144h1
skipping  mc144h2  : no best 
skipping  mc144j1  : no best 
mc144j2 432 of  1046 Best =  19.400000000000002
skipping specimen -  no trm acquisition data  mc144j2
mc144k1 433 of  1046 Best =  12.4
skipping specimen -  no trm acquisition data  mc144k1
skipping  mc145b1  : no best 
skipping  mc145c1  : no best 
mc145c2 436 of  1046 Best =  6.680000000000001
skipping specimen -  no trm acquisition data  mc145c2
mc145f1 437 of  1046 Best =  7.21
skipping specimen -  no trm acquisition data  mc145f1
skipping  mc145i1  : no best 
skipping  mc145j1  : no best 
mc145k2 440 of  1046 Best =  6.93
skipping specimen -  no trm acquisition data  mc145k2
mc145l1 441 of  1046 Best =  6.9399999999999995
skipping specimen -  no trm acquisition data  mc145l1
skipping  mc146a1  : no best 
skipping  mc146d1  : no best 
mc146e1 444 of  1046 Best =  16.7
skipping specimen -  no trm acquisition data  mc146e1
mc146f1 445 of  1046 Best =  17.7
skipping specimen -  no trm acquisition data  mc146f1
skipping  mc146h1  : no best 
skipping  mc146i2  : no best 
skipping  mc146j1  : no best 
mc146j2 449 of  1046 Best =  6.42
skipping specimen -  no trm acquisition data  mc146j2
skipping  mc146k1  : no best 
mc147a1 451 of  1046 Best =  26.400000000000002
skipping specimen -  no trm acquisition data  mc147a1
skipping  mc147c1  : no best 
mc147i1 453 of  1046 Best =  22.5
skipping specimen -  no trm acquisition data  mc147i1
mc147j2 454 of  1046 Best =  21.2
skipping specimen -  no trm acquisition data  mc147j2
mc147k2 455 of  1046 Best =  21.0
skipping specimen -  no trm acquisition data  mc147k2
skipping  mc148a1  : no best 
skipping  mc148b1  : no best 
skipping  mc148c1  : no best 
mc148d1 459 of  1046 Best =  53.4
skipping specimen -  no trm acquisition data  mc148d1
skipping  mc148f1  : no best 
mc148i1 461 of  1046 Best =  50.599999999999994
skipping specimen -  no trm acquisition data  mc148i1
mc148j1 462 of  1046 Best =  50.699999999999996
skipping specimen -  no trm acquisition data  mc148j1
skipping  mc148k1  : no best 
skipping  mc149a1  : no best 
skipping  mc149b1  : no best 
skipping  mc149d1  : no best 
skipping  mc149e1  : no best 
skipping  mc149g1  : no best 
skipping  mc14a  : no best 
mc14b 470 of  1046 Best =  70.7
skipping specimen -  no trm acquisition data  mc14b
mc14c 471 of  1046 Best =  39.5
skipping specimen -  no trm acquisition data  mc14c
mc14d 472 of  1046 Best =  54.6
skipping specimen -  no trm acquisition data  mc14d
skipping  mc14e  : no best 
skipping  mc14f  : no best 
skipping  mc14g  : no best 
mc14h 476 of  1046 Best =  83.1
skipping specimen -  no trm acquisition data  mc14h
skipping  mc150b1  : no best 
skipping  mc150c1  : no best 
skipping  mc150e1  : no best 
skipping  mc150f1  : no best 
skipping  mc150g1  : no best 
skipping  mc152a1  : no best 
skipping  mc152b1  : no best 
skipping  mc152b2  : no best 
skipping  mc152c1  : no best 
skipping  mc152e1  : no best 
skipping  mc152g1  : no best 
skipping  mc152i1  : no best 
skipping  mc152k1  : no best 
mc153a1 490 of  1046 Best =  29.8
skipping specimen -  no trm acquisition data  mc153a1
skipping  mc153a2  : no best 
mc153c1 492 of  1046 Best =  34.5
skipping specimen -  no trm acquisition data  mc153c1
skipping  mc153e1  : no best 
skipping  mc153i1  : no best 
skipping  mc153j1  : no best 
skipping  mc153m1  : no best 
skipping  mc154a1  : no best 
mc154a2 498 of  1046 Best =  8.64
skipping specimen -  no trm acquisition data  mc154a2
skipping  mc154b1  : no best 
skipping  mc154e1  : no best 
skipping  mc154f1  : no best 
skipping  mc154h1  : no best 
mc154j2 503 of  1046 Best =  7.300000000000001
skipping specimen -  no trm acquisition data  mc154j2
skipping  mc155a1  : no best 
skipping  mc155b1  : no best 
mc155c1 506 of  1046 Best =  34.199999999999996
skipping specimen -  no trm acquisition data  mc155c1
skipping  mc155e2  : no best 
skipping  mc155g1  : no best 
mc155h1 509 of  1046 Best =  26.5
skipping specimen -  no trm acquisition data  mc155h1
skipping  mc155i1  : no best 
mc155m1 511 of  1046 Best =  26.1
skipping specimen -  no trm acquisition data  mc155m1
skipping  mc156a1  : no best 
skipping  mc156b1  : no best 
skipping  mc156c1  : no best 
skipping  mc156c2  : no best 
skipping  mc156f1  : no best 
skipping  mc156g1  : no best 
skipping  mc156h1  : no best 
skipping  mc156i1  : no best 
skipping  mc157a1  : no best 
skipping  mc157a2  : no best 
skipping  mc157b1  : no best 
skipping  mc157b2  : no best 
mc157c2 524 of  1046 Best =  20.2
skipping specimen -  no trm acquisition data  mc157c2
skipping  mc157e2  : no best 
skipping  mc157f1  : no best 
skipping  mc157j1  : no best 
skipping  mc157k1  : no best 
mc158a1 529 of  1046 Best =  4.68
skipping specimen -  no trm acquisition data  mc158a1
mc158b1 530 of  1046 Best =  4.52
skipping specimen -  no trm acquisition data  mc158b1
skipping  mc158b2  : no best 
skipping  mc158c1  : no best 
skipping  mc158d1  : no best 
skipping  mc158f1  : no best 
skipping  mc158h1  : no best 
mc15a 536 of  1046 Best =  24.7
skipping specimen -  no trm acquisition data  mc15a
mc15b 537 of  1046 Best =  27.1
skipping specimen -  no trm acquisition data  mc15b
mc15c 538 of  1046 Best =  30.9
skipping specimen -  no trm acquisition data  mc15c
mc15c2 539 of  1046 Best =  29.099999999999998
skipping specimen -  no trm acquisition data  mc15c2
skipping  mc15d  : no best 
skipping  mc15e  : no best 
skipping  mc15f  : no best 
skipping  mc15g  : no best 
mc15h 544 of  1046 Best =  26.1
skipping specimen -  no trm acquisition data  mc15h
mc160a1 545 of  1046 Best =  20.9
skipping specimen -  no trm acquisition data  mc160a1
skipping  mc160a2  : no best 
skipping  mc160b1  : no best 
skipping  mc160c1  : no best 
mc160e1 549 of  1046 Best =  22.099999999999998
skipping specimen -  no trm acquisition data  mc160e1
skipping  mc160e2  : no best 
mc160f2 551 of  1046 Best =  22.7
skipping specimen -  no trm acquisition data  mc160f2
skipping  mc160h2  : no best 
skipping  mc160j1  : no best 
skipping  mc160j2  : no best 
skipping  mc161a1  : no best 
mc161b1 556 of  1046 Best =  5.800000000000001
skipping specimen -  no trm acquisition data  mc161b1
skipping  mc161e1  : no best 
skipping  mc161f1  : no best 
mc161g1 559 of  1046 Best =  4.1
skipping specimen -  no trm acquisition data  mc161g1
skipping  mc161j1  : no best 
skipping  mc161k1  : no best 
mc162b1 562 of  1046 Best =  7.29
skipping specimen -  no trm acquisition data  mc162b1
skipping  mc162b2  : no best 
mc162c1 564 of  1046 Best =  8.42
skipping specimen -  no trm acquisition data  mc162c1
skipping  mc162f1  : no best 
skipping  mc162g1  : no best 
skipping  mc162i1  : no best 
skipping  mc162j1  : no best 
skipping  mc163a1  : no best 
skipping  mc163b1  : no best 
skipping  mc163c1  : no best 
skipping  mc163d1  : no best 
skipping  mc163e1  : no best 
skipping  mc163f1  : no best 
skipping  mc163h1  : no best 
skipping  mc164a1  : no best 
skipping  mc164a2  : no best 
skipping  mc164a2-1  : no best 
skipping  mc164b1  : no best 
mc164c1 580 of  1046 Best =  81.4
skipping specimen -  no trm acquisition data  mc164c1
mc164f1 581 of  1046 Best =  81.19999999999999
skipping specimen -  no trm acquisition data  mc164f1
skipping  mc164g2  : no best 
skipping  mc164h1  : no best 
skipping  mc164i1  : no best 
mc164j1 585 of  1046 Best =  81.3
skipping specimen -  no trm acquisition data  mc164j1
skipping  mc164l2  : no best 
skipping  mc165a1  : no best 
mc165b1 588 of  1046 Best =  26.2
skipping specimen -  no trm acquisition data  mc165b1
skipping  mc165b2  : no best 
mc165c1 590 of  1046 Best =  24.2
skipping specimen -  no trm acquisition data  mc165c1
skipping  mc165c2  : no best 
skipping  mc165g1  : no best 
mc165h2 593 of  1046 Best =  26.400000000000002
skipping specimen -  no trm acquisition data  mc165h2
mc165i2 594 of  1046 Best =  28.3
skipping specimen -  no trm acquisition data  mc165i2
skipping  mc166a1  : no best 
mc166b1 596 of  1046 Best =  26.299999999999997
skipping specimen -  no trm acquisition data  mc166b1
skipping  mc166b2  : no best 
mc166c1 598 of  1046 Best =  22.0
skipping specimen -  no trm acquisition data  mc166c1
skipping  mc166c2  : no best 
mc166h2 600 of  1046 Best =  30.4
skipping specimen -  no trm acquisition data  mc166h2
skipping  mc166i1  : no best 
mc166i2 602 of  1046 Best =  37.7
skipping specimen -  no trm acquisition data  mc166i2
skipping  mc167a1  : no best 
mc167b1 604 of  1046 Best =  44.8
skipping specimen -  no trm acquisition data  mc167b1
mc167d2 605 of  1046 Best =  42.9
skipping specimen -  no trm acquisition data  mc167d2
skipping  mc167e1  : no best 
mc167e2 607 of  1046 Best =  42.5
skipping specimen -  no trm acquisition data  mc167e2
skipping  mc167f2  : no best 
skipping  mc167h1  : no best 
skipping  mc167j1  : no best 
mc167k1 611 of  1046 Best =  42.7
skipping specimen -  no trm acquisition data  mc167k1
mc168a1 612 of  1046 Best =  5.83
skipping specimen -  no trm acquisition data  mc168a1
skipping  mc168c1  : no best 
mc168c2 614 of  1046 Best =  5.26
skipping specimen -  no trm acquisition data  mc168c2
mc168d1 615 of  1046 Best =  5.9
skipping specimen -  no trm acquisition data  mc168d1
mc168f1 616 of  1046 Best =  5.49
skipping specimen -  no trm acquisition data  mc168f1
skipping  mc168h1  : no best 
mc168h2 618 of  1046 Best =  5.2
skipping specimen -  no trm acquisition data  mc168h2
skipping  mc168i1  : no best 
skipping  mc168j1  : no best 
skipping  mc168k1  : no best 
skipping  mc170a1  : no best 
skipping  mc170c2  : no best 
skipping  mc170d1  : no best 
skipping  mc170e2  : no best 
skipping  mc170f1  : no best 
skipping  mc19a  : no best 
mc19b 628 of  1046 Best =  25.2
skipping specimen -  no trm acquisition data  mc19b
skipping  mc19c  : no best 
skipping  mc19d  : no best 
skipping  mc19e  : no best 
skipping  mc19f  : no best 
skipping  mc19g  : no best 
skipping  mc200a1  : no best 
skipping  mc200a2  : no best 
mc200b1 636 of  1046 Best =  15.2
skipping specimen -  no trm acquisition data  mc200b1
skipping  mc200b2  : no best 
mc200c1 638 of  1046 Best =  14.8
skipping specimen -  no trm acquisition data  mc200c1
skipping  mc200c2  : no best 
mc200d1 640 of  1046 Best =  11.600000000000001
skipping specimen -  no trm acquisition data  mc200d1
skipping  mc200d2  : no best 
mc200h1 642 of  1046 Best =  9.9
skipping specimen -  no trm acquisition data  mc200h1
mc200i1 643 of  1046 Best =  12.9
skipping specimen -  no trm acquisition data  mc200i1
skipping  mc201a1  : no best 
mc201b1 645 of  1046 Best =  4.68
skipping specimen -  no trm acquisition data  mc201b1
skipping  mc201b2  : no best 
skipping  mc201c1  : no best 
skipping  mc201d1  : no best 
skipping  mc201e1  : no best 
skipping  mc201j1  : no best 
skipping  mc202a1  : no best 
mc202b1 652 of  1046 Best =  2.06
skipping specimen -  no trm acquisition data  mc202b1
skipping  mc202c1  : no best 
skipping  mc202d1  : no best 
skipping  mc202f1  : no best 
skipping  mc202h1  : no best 
skipping  mc202j1  : no best 
skipping  mc203a1  : no best 
skipping  mc203b1  : no best 
skipping  mc203c1  : no best 
skipping  mc203d1  : no best 
skipping  mc203g1  : no best 
skipping  mc203h1  : no best 
skipping  mc204a1  : no best 
mc204b1 665 of  1046 Best =  21.5
skipping specimen -  no trm acquisition data  mc204b1
skipping  mc204c1  : no best 
skipping  mc204h1  : no best 
skipping  mc204k1  : no best 
skipping  mc204l1  : no best 
skipping  mc205a1  : no best 
skipping  mc205a1-1  : no best 
mc205a2 672 of  1046 Best =  43.2
skipping specimen -  no trm acquisition data  mc205a2
mc205b1 673 of  1046 Best =  30.3
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 119
         Function evaluations: 227
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 47
         Function evaluations: 90
Banc=  30.303352800307902
1  saved in  mc205b1_TRM.png
skipping  mc205c1  : no best 
skipping  mc205d1  : no best 
skipping  mc205e1  : no best 
mc205h1 677 of  1046 Best =  54.8
skipping specimen -  no trm acquisition data  mc205h1
skipping  mc205h2  : no best 
mc205i2 679 of  1046 Best =  46.3
skipping specimen -  no trm acquisition data  mc205i2
mc205k1 680 of  1046 Best =  57.3
skipping specimen -  no trm acquisition data  mc205k1
skipping  mc206a1  : no best 
mc206b1 682 of  1046 Best =  77.7
skipping specimen -  no trm acquisition data  mc206b1
mc206c1 683 of  1046 Best =  95.1
skipping specimen -  no trm acquisition data  mc206c1
mc206d1 684 of  1046 Best =  115.89
skipping specimen -  no trm acquisition data  mc206d1
mc206e1 685 of  1046 Best =  142.6
skipping specimen -  no trm acquisition data  mc206e1
mc206f1 686 of  1046 Best =  117.67
skipping specimen -  no trm acquisition data  mc206f1
skipping  mc206g1  : no best 
skipping  mc206h1  : no best 
skipping  mc206i1  : no best 
skipping  mc206k1  : no best 
skipping  mc207a1  : no best 
skipping  mc207b1  : no best 
skipping  mc207d1  : no best 
skipping  mc207g2  : no best 
skipping  mc207h2  : no best 
skipping  mc207k2  : no best 
skipping  mc208a1  : no best 
mc208b1 698 of  1046 Best =  23.0
skipping specimen -  no trm acquisition data  mc208b1
skipping  mc208c2  : no best 
skipping  mc208d2  : no best 
skipping  mc208e2  : no best 
skipping  mc208f2  : no best 
skipping  mc209a1  : no best 
skipping  mc209b1  : no best 
skipping  mc209b2  : no best 
skipping  mc209c2  : no best 
skipping  mc209e2  : no best 
skipping  mc209f1  : no best 
skipping  mc20a  : no best 
skipping  mc20b  : no best 
skipping  mc20c  : no best 
mc20d 712 of  1046 Best =  19.400000000000002
skipping specimen -  no trm acquisition data  mc20d
skipping  mc20e  : no best 
skipping  mc20f  : no best 
mc20h 715 of  1046 Best =  6.19
skipping specimen -  no trm acquisition data  mc20h
skipping  mc210a2  : no best 
skipping  mc210b1  : no best 
skipping  mc210b2  : no best 
skipping  mc210c2  : no best 
skipping  mc210e1  : no best 
skipping  mc210i2  : no best 
skipping  mc211a1  : no best 
mc211b1 723 of  1046 Best =  96.8
skipping specimen -  no trm acquisition data  mc211b1
skipping  mc211b2  : no best 
mc211e1 725 of  1046 Best =  75.2
skipping specimen -  no trm acquisition data  mc211e1
skipping  mc211e2  : no best 
mc211g1 727 of  1046 Best =  73.6
skipping specimen -  no trm acquisition data  mc211g1
skipping  mc211g2  : no best 
mc211h1 729 of  1046 Best =  89.5
skipping specimen -  no trm acquisition data  mc211h1
mc211i1 730 of  1046 Best =  72.3
skipping specimen -  no trm acquisition data  mc211i1
skipping  mc212a1  : no best 
skipping  mc212b1  : no best 
skipping  mc212b2  : no best 
skipping  mc212c2  : no best 
skipping  mc212d2  : no best 
skipping  mc212g2  : no best 
skipping  mc213b1  : no best 
skipping  mc213e2  : no best 
skipping  mc213f2  : no best 
skipping  mc213g2  : no best 
skipping  mc213h2  : no best 
skipping  mc213i2  : no best 
skipping  mc214a2  : no best 
mc214b1 744 of  1046 Best =  48.8
skipping specimen -  no trm acquisition data  mc214b1
skipping  mc214b2  : no best 
mc214d1 746 of  1046 Best =  42.8
skipping specimen -  no trm acquisition data  mc214d1
skipping  mc214d2  : no best 
mc214g1 748 of  1046 Best =  43.800000000000004
skipping specimen -  no trm acquisition data  mc214g1
skipping  mc214g2  : no best 
mc214h1 750 of  1046 Best =  43.300000000000004
skipping specimen -  no trm acquisition data  mc214h1
mc214j1 751 of  1046 Best =  40.3
skipping specimen -  no trm acquisition data  mc214j1
skipping  mc214j2  : no best 
mc215a1 753 of  1046 Best =  51.199999999999996
skipping specimen -  no trm acquisition data  mc215a1
skipping  mc215a2  : no best 
mc215b1 755 of  1046 Best =  50.800000000000004
skipping specimen -  no trm acquisition data  mc215b1
mc215c1 756 of  1046 Best =  16.2
skipping specimen -  no trm acquisition data  mc215c1
skipping  mc215c2  : no best 
mc215d1 758 of  1046 Best =  11.8
skipping specimen -  no trm acquisition data  mc215d1
skipping  mc215d2  : no best 
mc215h1 760 of  1046 Best =  17.0
skipping specimen -  no trm acquisition data  mc215h1
skipping  mc215h2  : no best 
skipping  mc215i1  : no best 
mc216a1 763 of  1046 Best =  4.74
skipping specimen -  no trm acquisition data  mc216a1
skipping  mc216a2  : no best 
mc216b1 765 of  1046 Best =  5.52
skipping specimen -  no trm acquisition data  mc216b1
mc216c1 766 of  1046 Best =  4.21
skipping specimen -  no trm acquisition data  mc216c1
skipping  mc216c2  : no best 
skipping  mc216f1  : no best 
skipping  mc216f2  : no best 
skipping  mc216g1  : no best 
skipping  mc216g2  : no best 
skipping  mc216h2  : no best 
mc217a1 773 of  1046 Best =  27.1
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 88
         Function evaluations: 169
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 45
         Function evaluations: 88
Banc=  27.033927949582854
1  saved in  mc217a1_TRM.png
skipping  mc217a2  : no best 
skipping  mc217a2-1  : no best 
mc217b1 776 of  1046 Best =  25.299999999999997
skipping specimen -  no trm acquisition data  mc217b1
skipping  mc217b2  : no best 
mc217c1 778 of  1046 Best =  35.9
skipping specimen -  no trm acquisition data  mc217c1
skipping  mc217c2  : no best 
mc217d1 780 of  1046 Best =  28.900000000000002
skipping specimen -  no trm acquisition data  mc217d1
skipping  mc217d2  : no best 
mc217e1 782 of  1046 Best =  34.400000000000006
skipping specimen -  no trm acquisition data  mc217e1
skipping  mc217e2  : no best 
mc218a1 784 of  1046 Best =  37.0
skipping specimen -  no trm acquisition data  mc218a1
skipping  mc218a2  : no best 
mc218b1 786 of  1046 Best =  33.4
skipping specimen -  no trm acquisition data  mc218b1
skipping  mc218b2  : no best 
mc218d1 788 of  1046 Best =  35.800000000000004
skipping specimen -  no trm acquisition data  mc218d1
skipping  mc218d2  : no best 
mc218i1 790 of  1046 Best =  30.5
skipping specimen -  no trm acquisition data  mc218i1
skipping  mc218i2  : no best 
mc218j1 792 of  1046 Best =  34.8
skipping specimen -  no trm acquisition data  mc218j1
skipping  mc218j2  : no best 
mc219a1 794 of  1046 Best =  33.4
skipping specimen -  no trm acquisition data  mc219a1
skipping  mc219a2  : no best 
mc219b1 796 of  1046 Best =  34.7
skipping specimen -  no trm acquisition data  mc219b1
skipping  mc219b2  : no best 
mc219c1 798 of  1046 Best =  27.7
skipping specimen -  no trm acquisition data  mc219c1
skipping  mc219c2  : no best 
mc219d1 800 of  1046 Best =  26.2
skipping specimen -  no trm acquisition data  mc219d1
skipping  mc219d2  : no best 
mc219e1 802 of  1046 Best =  33.599999999999994
skipping specimen -  no trm acquisition data  mc219e1
skipping  mc219e2  : no best 
mc21a 804 of  1046 Best =  48.300000000000004
skipping specimen -  no trm acquisition data  mc21a
mc21b 805 of  1046 Best =  44.5
skipping specimen -  no trm acquisition data  mc21b
mc21c 806 of  1046 Best =  46.9
skipping specimen -  no trm acquisition data  mc21c
skipping  mc21d  : no best 
mc21e 808 of  1046 Best =  40.5
skipping specimen -  no trm acquisition data  mc21e
skipping  mc21f  : no best 
skipping  mc21g  : no best 
skipping  mc21h  : no best 
mc220a1 812 of  1046 Best =  54.2
skipping specimen -  no trm acquisition data  mc220a1
skipping  mc220a2  : no best 
mc220b1 814 of  1046 Best =  54.9
skipping specimen -  no trm acquisition data  mc220b1
skipping  mc220b2  : no best 
mc220c1 816 of  1046 Best =  53.0
skipping specimen -  no trm acquisition data  mc220c1
skipping  mc220c2  : no best 
mc220d1 818 of  1046 Best =  55.099999999999994
skipping specimen -  no trm acquisition data  mc220d1
skipping  mc220d2  : no best 
mc220e1 820 of  1046 Best =  52.800000000000004
skipping specimen -  no trm acquisition data  mc220e1
skipping  mc220f2  : no best 
skipping  mc221b1  : no best 
skipping  mc221c1  : no best 
skipping  mc221d2  : no best 
skipping  mc221h2  : no best 
skipping  mc221i2  : no best 
skipping  mc221j2  : no best 
skipping  mc222a1  : no best 
mc222b1 829 of  1046 Best =  12.700000000000001
skipping specimen -  no trm acquisition data  mc222b1
skipping  mc222c1  : no best 
skipping  mc222e1  : no best 
skipping  mc222h2  : no best 
skipping  mc222j2  : no best 
mc223a1 834 of  1046 Best =  21.5
skipping specimen -  no trm acquisition data  mc223a1
skipping  mc223a2  : no best 
mc223b1 836 of  1046 Best =  21.5
skipping specimen -  no trm acquisition data  mc223b1
skipping  mc223c1  : no best 
mc223c2 838 of  1046 Best =  24.8
skipping specimen -  no trm acquisition data  mc223c2
skipping  mc223d1  : no best 
skipping  mc223e1  : no best 
skipping  mc223f1  : no best 
mc223g1 842 of  1046 Best =  18.3
skipping specimen -  no trm acquisition data  mc223g1
mc223l1 843 of  1046 Best =  16.5
skipping specimen -  no trm acquisition data  mc223l1
skipping  mc224a1  : no best 
skipping  mc224b1  : no best 
skipping  mc224b2  : no best 
skipping  mc224c2  : no best 
skipping  mc224e2  : no best 
skipping  mc224f2  : no best 
mc225a1 850 of  1046 Best =  25.5
skipping specimen -  no trm acquisition data  mc225a1
skipping  mc225a2  : no best 
mc225b1 852 of  1046 Best =  25.8
skipping specimen -  no trm acquisition data  mc225b1
mc225c1 853 of  1046 Best =  26.0
skipping specimen -  no trm acquisition data  mc225c1
skipping  mc225c2  : no best 
mc225d1 855 of  1046 Best =  30.4
skipping specimen -  no trm acquisition data  mc225d1
skipping  mc225d2  : no best 
skipping  mc225f2  : no best 
skipping  mc225g2  : no best 
mc225i1 859 of  1046 Best =  32.0
skipping specimen -  no trm acquisition data  mc225i1
skipping  mc226a1  : no best 
mc226b1 861 of  1046 Best =  25.299999999999997
skipping specimen -  no trm acquisition data  mc226b1
skipping  mc226b2  : no best 
skipping  mc226d2  : no best 
skipping  mc226f2  : no best 
skipping  mc226g2  : no best 
mc227b1 866 of  1046 Best =  14.9
skipping specimen -  no trm acquisition data  mc227b1
skipping  mc227b2  : no best 
skipping  mc227c2  : no best 
skipping  mc227d2  : no best 
skipping  mc227f2  : no best 
skipping  mc227h2  : no best 
mc228a1 872 of  1046 Best =  10.6
skipping specimen -  no trm acquisition data  mc228a1
skipping  mc228a2  : no best 
mc228b1 874 of  1046 Best =  10.6
skipping specimen -  no trm acquisition data  mc228b1
skipping  mc228b2  : no best 
mc228d1 876 of  1046 Best =  13.200000000000001
skipping specimen -  no trm acquisition data  mc228d1
skipping  mc228d2  : no best 
mc228e1 878 of  1046 Best =  12.3
skipping specimen -  no trm acquisition data  mc228e1
skipping  mc228e2  : no best 
mc228g1 880 of  1046 Best =  17.3
skipping specimen -  no trm acquisition data  mc228g1
skipping  mc228g2  : no best 
skipping  mc229a2  : no best 
skipping  mc229b1  : no best 
skipping  mc229b2  : no best 
skipping  mc229e2  : no best 
mc229g1 886 of  1046 Best =  34.199999999999996
skipping specimen -  no trm acquisition data  mc229g1
skipping  mc229g2  : no best 
mc229h1 888 of  1046 Best =  26.8
skipping specimen -  no trm acquisition data  mc229h1
skipping  mc229h2  : no best 
mc229i1 890 of  1046 Best =  30.4
skipping specimen -  no trm acquisition data  mc229i1
mc229k1 891 of  1046 Best =  32.7
skipping specimen -  no trm acquisition data  mc229k1
mc26a 892 of  1046 Best =  38.5
skipping specimen -  no trm acquisition data  mc26a
skipping  mc26b  : no best 
mc26c 894 of  1046 Best =  22.799999999999997
skipping specimen -  no trm acquisition data  mc26c
mc26d 895 of  1046 Best =  32.5
skipping specimen -  no trm acquisition data  mc26d
mc26e 896 of  1046 Best =  58.400000000000006
skipping specimen -  no trm acquisition data  mc26e
skipping  mc26f  : no best 
skipping  mc26g  : no best 
skipping  mc26h  : no best 
mc28a 900 of  1046 Best =  27.1
skipping specimen -  no trm acquisition data  mc28a
mc28b 901 of  1046 Best =  12.9
skipping specimen -  no trm acquisition data  mc28b
mc28c 902 of  1046 Best =  25.700000000000003
skipping specimen -  no trm acquisition data  mc28c
skipping  mc28d  : no best 
skipping  mc28e  : no best 
mc28f 905 of  1046 Best =  29.3
skipping specimen -  no trm acquisition data  mc28f
skipping  mc28g  : no best 
skipping  mc28h  : no best 
skipping  mc29a  : no best 
skipping  mc29b  : no best 
skipping  mc29c  : no best 
mc29d 911 of  1046 Best =  30.4
skipping specimen -  no trm acquisition data  mc29d
skipping  mc29e  : no best 
skipping  mc29f  : no best 
skipping  mc29g  : no best 
skipping  mc29h  : no best 
mc30a 916 of  1046 Best =  42.8
skipping specimen -  no trm acquisition data  mc30a
mc30b 917 of  1046 Best =  42.2
skipping specimen -  no trm acquisition data  mc30b
skipping  mc30c  : no best 
mc30d 919 of  1046 Best =  42.5
skipping specimen -  no trm acquisition data  mc30d
mc30e 920 of  1046 Best =  43.099999999999994
skipping specimen -  no trm acquisition data  mc30e
skipping  mc30f  : no best 
skipping  mc30g  : no best 
skipping  mc30h  : no best 
mc31b 924 of  1046 Best =  14.0
skipping specimen -  no trm acquisition data  mc31b
skipping  mc31c  : no best 
skipping  mc31d  : no best 
skipping  mc31f  : no best 
skipping  mc31h  : no best 
mc32a 929 of  1046 Best =  29.4
skipping specimen -  no trm acquisition data  mc32a
mc32b 930 of  1046 Best =  32.1
skipping specimen -  no trm acquisition data  mc32b
skipping  mc32c  : no best 
mc32d 932 of  1046 Best =  39.7
skipping specimen -  no trm acquisition data  mc32d
mc32e 933 of  1046 Best =  28.099999999999998
skipping specimen -  no trm acquisition data  mc32e
skipping  mc32f  : no best 
skipping  mc32g  : no best 
skipping  mc32h  : no best 
skipping  mc33a  : no best 
mc33b 938 of  1046 Best =  37.3
skipping specimen -  no trm acquisition data  mc33b
mc33c 939 of  1046 Best =  32.1
skipping specimen -  no trm acquisition data  mc33c
skipping  mc33d  : no best 
mc33e 941 of  1046 Best =  32.3
skipping specimen -  no trm acquisition data  mc33e
skipping  mc33f  : no best 
skipping  mc33g  : no best 
skipping  mc33h  : no best 
skipping  mc34a  : no best 
skipping  mc34b  : no best 
mc34c 947 of  1046 Best =  23.0
skipping specimen -  no trm acquisition data  mc34c
skipping  mc34d  : no best 
skipping  mc34e  : no best 
skipping  mc34f  : no best 
skipping  mc34h  : no best 
mc35a 952 of  1046 Best =  23.8
skipping specimen -  no trm acquisition data  mc35a
mc35b 953 of  1046 Best =  22.2
skipping specimen -  no trm acquisition data  mc35b
mc35c 954 of  1046 Best =  23.3
skipping specimen -  no trm acquisition data  mc35c
mc35d 955 of  1046 Best =  26.1
skipping specimen -  no trm acquisition data  mc35d
skipping  mc35e  : no best 
skipping  mc35f  : no best 
skipping  mc35g  : no best 
skipping  mc35h  : no best 
mc36a 960 of  1046 Best =  29.8
skipping specimen -  no trm acquisition data  mc36a
mc36b 961 of  1046 Best =  25.1
skipping specimen -  no trm acquisition data  mc36b
skipping  mc36c  : no best 
skipping  mc36d  : no best 
mc36e 964 of  1046 Best =  22.799999999999997
skipping specimen -  no trm acquisition data  mc36e
skipping  mc36f  : no best 
skipping  mc36g  : no best 
mc36h 967 of  1046 Best =  25.0
skipping specimen -  no trm acquisition data  mc36h
skipping  mc37a  : no best 
skipping  mc37b  : no best 
mc37c 970 of  1046 Best =  62.8
skipping specimen -  no trm acquisition data  mc37c
mc37d 971 of  1046 Best =  52.5
skipping specimen -  no trm acquisition data  mc37d
mc37e 972 of  1046 Best =  62.5
skipping specimen -  no trm acquisition data  mc37e
skipping  mc37f  : no best 
skipping  mc37g  : no best 
mc37h 975 of  1046 Best =  63.6
skipping specimen -  no trm acquisition data  mc37h
skipping  mc38a  : no best 
skipping  mc38b  : no best 
skipping  mc38c  : no best 
skipping  mc38e  : no best 
skipping  mc38f  : no best 
mc38g 981 of  1046 Best =  28.4
skipping specimen -  no trm acquisition data  mc38g
skipping  mc38h  : no best 
mc39a 983 of  1046 Best =  26.0
skipping specimen -  no trm acquisition data  mc39a
mc39b 984 of  1046 Best =  33.699999999999996
skipping specimen -  no trm acquisition data  mc39b
mc39c 985 of  1046 Best =  22.099999999999998
skipping specimen -  no trm acquisition data  mc39c
skipping  mc39d  : no best 
skipping  mc39e  : no best 
skipping  mc39f  : no best 
skipping  mc39g  : no best 
skipping  mc39h  : no best 
skipping  mc40a  : no best 
skipping  mc40b  : no best 
skipping  mc40c  : no best 
mc40e 994 of  1046 Best =  39.400000000000006
skipping specimen -  no trm acquisition data  mc40e
skipping  mc40f  : no best 
skipping  mc40g  : no best 
skipping  mc40h  : no best 
skipping  mc41a  : no best 
skipping  mc41b  : no best 
skipping  mc41c  : no best 
skipping  mc41d  : no best 
skipping  mc41e  : no best 
skipping  mc41f  : no best 
skipping  mc41h  : no best 
skipping  mc42b  : no best 
skipping  mc42c  : no best 
skipping  mc42d  : no best 
skipping  mc42f  : no best 
skipping  mc42h  : no best 
skipping  mc43a  : no best 
skipping  mc43b  : no best 
skipping  mc43c  : no best 
skipping  mc43e  : no best 
mc43f 1014 of  1046 Best =  11.8
skipping specimen -  no trm acquisition data  mc43f
skipping  mc43g  : no best 
mc44a 1016 of  1046 Best =  32.6
skipping specimen -  no trm acquisition data  mc44a
mc44b 1017 of  1046 Best =  25.0
skipping specimen -  no trm acquisition data  mc44b
skipping  mc44c  : no best 
skipping  mc44d  : no best 
skipping  mc44e  : no best 
skipping  mc44f  : no best 
mc44g 1022 of  1046 Best =  12.0
skipping specimen -  no trm acquisition data  mc44g
mc44h 1023 of  1046 Best =  17.0
skipping specimen -  no trm acquisition data  mc44h
skipping  mc48a  : no best 
skipping  mc48b  : no best 
skipping  mc48c  : no best 
skipping  mc48d  : no best 
skipping  mc48e  : no best 
mc48f 1029 of  1046 Best =  15.400000000000002
skipping specimen -  no trm acquisition data  mc48f
mc48g 1030 of  1046 Best =  15.0
skipping specimen -  no trm acquisition data  mc48g
skipping  mc48h  : no best 
skipping  mc49a  : no best 
skipping  mc49b  : no best 
skipping  mc49c  : no best 
skipping  mc49d  : no best 
skipping  mc49e  : no best 
skipping  mc49g  : no best 
skipping  mc49h  : no best 
mc50a 1039 of  1046 Best =  35.7
skipping specimen -  no trm acquisition data  mc50a
mc50b 1040 of  1046 Best =  34.0
skipping specimen -  no trm acquisition data  mc50b
skipping  mc50c  : no best 
skipping  mc50d  : no best 
mc50e 1043 of  1046 Best =  34.0
skipping specimen -  no trm acquisition data  mc50e
mc50f 1044 of  1046 Best =  31.2
skipping specimen -  no trm acquisition data  mc50f
skipping  mc50g  : no best 
skipping  mc50h  : no best 
6  records written to file  NLT_specimens.txt
In [228]:
Image("mc117b1_TRM.png")
Out[228]:
In [229]:
!rm mc117b1_TRM.png
!trmaq_magic.py -ft data_files/2_5/McMurdo/pmag_specimens.txt \
    -f data_files/2_5/McMurdo/magic_measurements.txt -sav -fmt png -DM 2
mc01a 1 of  1046 Best =  13.481
skipping specimen -  no trm acquisition data  mc01a
mc01b 2 of  1046 Best =  13.85
skipping specimen -  no trm acquisition data  mc01b
skipping  mc01c  : no best 
mc01d 4 of  1046 Best =  18.708000000000002
skipping specimen -  no trm acquisition data  mc01d
skipping  mc01e  : no best 
skipping  mc01f  : no best 
mc01g 7 of  1046 Best =  20.125
skipping specimen -  no trm acquisition data  mc01g
skipping  mc01h  : no best 
skipping  mc02a  : no best 
skipping  mc02b  : no best 
skipping  mc02c  : no best 
skipping  mc02e  : no best 
mc02f 13 of  1046 Best =  16.748
skipping specimen -  no trm acquisition data  mc02f
skipping  mc02g  : no best 
skipping  mc02h  : no best 
skipping  mc03a  : no best 
skipping  mc03b  : no best 
skipping  mc03c  : no best 
skipping  mc03d  : no best 
skipping  mc03f  : no best 
skipping  mc03h  : no best 
skipping  mc04a  : no best 
skipping  mc04b  : no best 
skipping  mc04c-1  : no best 
skipping  mc04e  : no best 
skipping  mc04f  : no best 
skipping  mc04g  : no best 
skipping  mc04h  : no best 
skipping  mc06a  : no best 
skipping  mc06c  : no best 
skipping  mc06d  : no best 
skipping  mc06g  : no best 
mc06h 33 of  1046 Best =  27.673000000000002
skipping specimen -  no trm acquisition data  mc06h
skipping  mc07b  : no best 
skipping  mc07c  : no best 
skipping  mc07d  : no best 
skipping  mc07e  : no best 
skipping  mc07f  : no best 
mc08a 39 of  1046 Best =  44.894
skipping specimen -  no trm acquisition data  mc08a
mc08b 40 of  1046 Best =  41.879
skipping specimen -  no trm acquisition data  mc08b
skipping  mc08c  : no best 
skipping  mc08d  : no best 
skipping  mc08e  : no best 
skipping  mc08f  : no best 
mc08g 45 of  1046 Best =  43.302
skipping specimen -  no trm acquisition data  mc08g
mc08h 46 of  1046 Best =  43.998000000000005
skipping specimen -  no trm acquisition data  mc08h
mc09a 47 of  1046 Best =  27.135
skipping specimen -  no trm acquisition data  mc09a
mc09b 48 of  1046 Best =  26.078999999999997
skipping specimen -  no trm acquisition data  mc09b
skipping  mc09c  : no best 
mc09d 50 of  1046 Best =  28.092000000000002
skipping specimen -  no trm acquisition data  mc09d
skipping  mc09e  : no best 
skipping  mc09f  : no best 
skipping  mc09g  : no best 
skipping  mc09h  : no best 
skipping  mc100a1  : no best 
skipping  mc100d1  : no best 
skipping  mc100e1  : no best 
skipping  mc100e2  : no best 
skipping  mc100f2  : no best 
skipping  mc100g1  : no best 
skipping  mc100g2  : no best 
skipping  mc100h2  : no best 
skipping  mc101a1  : no best 
skipping  mc101b1  : no best 
skipping  mc101c1  : no best 
skipping  mc101d1  : no best 
skipping  mc101f1  : no best 
skipping  mc101h1  : no best 
skipping  mc102a1  : no best 
skipping  mc102a2  : no best 
skipping  mc102b1  : no best 
skipping  mc102b2  : no best 
skipping  mc102e1  : no best 
skipping  mc102f1  : no best 
skipping  mc102g1  : no best 
skipping  mc102m2  : no best 
skipping  mc103a1  : no best 
skipping  mc103a2  : no best 
skipping  mc103b1  : no best 
skipping  mc103b2  : no best 
skipping  mc103c1  : no best 
skipping  mc103c2  : no best 
skipping  mc103d1  : no best 
skipping  mc103d2  : no best 
mc103e1 85 of  1046 Best =  21.005
skipping specimen -  no trm acquisition data  mc103e1
skipping  mc103e2  : no best 
skipping  mc104a1  : no best 
skipping  mc104b1  : no best 
skipping  mc104b2  : no best 
skipping  mc104c1  : no best 
skipping  mc104c2  : no best 
skipping  mc104d1  : no best 
skipping  mc104f1  : no best 
skipping  mc105a1  : no best 
mc105a2 95 of  1046 Best =  27.07
skipping specimen -  no trm acquisition data  mc105a2
mc105c1 96 of  1046 Best =  28.4
skipping specimen -  no trm acquisition data  mc105c1
mc105d1 97 of  1046 Best =  27.636000000000003
skipping specimen -  no trm acquisition data  mc105d1
skipping  mc105f1  : no best 
skipping  mc105g1  : no best 
skipping  mc105h1  : no best 
mc105j1 101 of  1046 Best =  31.377000000000002
skipping specimen -  no trm acquisition data  mc105j1
skipping  mc106a1  : no best 
skipping  mc106b1  : no best 
skipping  mc106c1  : no best 
skipping  mc106d1  : no best 
skipping  mc106e1  : no best 
skipping  mc107c1  : no best 
skipping  mc107d2  : no best 
skipping  mc107e1  : no best 
mc107e2 110 of  1046 Best =  15.24
skipping specimen -  no trm acquisition data  mc107e2
skipping  mc107h1  : no best 
skipping  mc107k1  : no best 
skipping  mc107l1  : no best 
skipping  mc108a1  : no best 
skipping  mc108a2  : no best 
skipping  mc108b1  : no best 
skipping  mc108c1  : no best 
skipping  mc108d1  : no best 
skipping  mc108g2  : no best 
skipping  mc108h1  : no best 
skipping  mc108k1  : no best 
mc109a1 122 of  1046 Best =  35.957
skipping specimen -  no trm acquisition data  mc109a1
skipping  mc109a2  : no best 
mc109c1 124 of  1046 Best =  34.801
skipping specimen -  no trm acquisition data  mc109c1
mc109d1 125 of  1046 Best =  33.654
skipping specimen -  no trm acquisition data  mc109d1
mc109e1 126 of  1046 Best =  30.343
skipping specimen -  no trm acquisition data  mc109e1
skipping  mc109i1  : no best 
mc10a 128 of  1046 Best =  29.544
skipping specimen -  no trm acquisition data  mc10a
mc10b 129 of  1046 Best =  29.657
skipping specimen -  no trm acquisition data  mc10b
skipping  mc10c  : no best 
mc10d 131 of  1046 Best =  37.372
skipping specimen -  no trm acquisition data  mc10d
skipping  mc10e  : no best 
skipping  mc10f  : no best 
skipping  mc10g  : no best 
skipping  mc10h  : no best 
skipping  mc110a1  : no best 
skipping  mc110a2  : no best 
skipping  mc110b1  : no best 
skipping  mc110b2  : no best 
skipping  mc110d1  : no best 
skipping  mc110g1  : no best 
skipping  mc110i1  : no best 
skipping  mc111a2  : no best 
skipping  mc111b1  : no best 
skipping  mc111d1  : no best 
mc111d2 146 of  1046 Best =  27.594
skipping specimen -  no trm acquisition data  mc111d2
skipping  mc111e1  : no best 
mc111e2 148 of  1046 Best =  28.201999999999998
skipping specimen -  no trm acquisition data  mc111e2
skipping  mc111f1  : no best 
skipping  mc111l1  : no best 
skipping  mc112a1  : no best 
skipping  mc112b2  : no best 
skipping  mc112c1  : no best 
skipping  mc112c2  : no best 
skipping  mc112d1  : no best 
skipping  mc112g1  : no best 
skipping  mc112h3  : no best 
skipping  mc112j1  : no best 
skipping  mc113a1  : no best 
skipping  mc113a1-1  : no best 
mc113a2 161 of  1046 Best =  10.962
skipping specimen -  no trm acquisition data  mc113a2
skipping  mc113b1  : no best 
skipping  mc113c1  : no best 
skipping  mc113e1  : no best 
skipping  mc113f1  : no best 
skipping  mc113g1  : no best 
skipping  mc113h1  : no best 
mc113j1 168 of  1046 Best =  11.495
skipping specimen -  no trm acquisition data  mc113j1
mc113m1 169 of  1046 Best =  12.136999999999999
skipping specimen -  no trm acquisition data  mc113m1
skipping  mc114a1  : no best 
skipping  mc114b2  : no best 
skipping  mc114c1  : no best 
skipping  mc114d2  : no best 
skipping  mc114e1  : no best 
skipping  mc114i1  : no best 
skipping  mc115a1  : no best 
mc115a2 177 of  1046 Best =  24.91
skipping specimen -  no trm acquisition data  mc115a2
mc115b1 178 of  1046 Best =  24.302
skipping specimen -  no trm acquisition data  mc115b1
mc115e1 179 of  1046 Best =  24.723
skipping specimen -  no trm acquisition data  mc115e1
skipping  mc115g2  : no best 
skipping  mc115h1  : no best 
skipping  mc116a1  : no best 
mc116b1 183 of  1046 Best =  38.525
skipping specimen -  no trm acquisition data  mc116b1
skipping  mc116c1  : no best 
skipping  mc116i2  : no best 
mc116j2 186 of  1046 Best =  41.015
skipping specimen -  no trm acquisition data  mc116j2
mc117a1 187 of  1046 Best =  25.500999999999998
skipping specimen -  no trm acquisition data  mc117a1
skipping  mc117a2  : no best 
skipping  mc117a2-1  : no best 
mc117b1 190 of  1046 Best =  26.183999999999997
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 111
         Function evaluations: 209
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 49
         Function evaluations: 92
Banc=  26.19814668726823
1  saved in  mc117b1_TRM.png
mc117d2 191 of  1046 Best =  26.787999999999997
skipping specimen -  no trm acquisition data  mc117d2
mc117e2 192 of  1046 Best =  27.157
skipping specimen -  no trm acquisition data  mc117e2
skipping  mc117h1  : no best 
skipping  mc118a1  : no best 
skipping  mc118c1  : no best 
skipping  mc118d1  : no best 
skipping  mc118e1  : no best 
skipping  mc118f1  : no best 
skipping  mc118i1  : no best 
skipping  mc118l2  : no best 
mc119a1 201 of  1046 Best =  42.403
skipping specimen -  no trm acquisition data  mc119a1
mc119b1 202 of  1046 Best =  43.595
skipping specimen -  no trm acquisition data  mc119b1
skipping  mc119b2  : no best 
mc119d2 204 of  1046 Best =  39.053
skipping specimen -  no trm acquisition data  mc119d2
mc119e2 205 of  1046 Best =  40.25
skipping specimen -  no trm acquisition data  mc119e2
mc119f2 206 of  1046 Best =  39.545
skipping specimen -  no trm acquisition data  mc119f2
skipping  mc11a  : no best 
mc11b 208 of  1046 Best =  48.107
skipping specimen -  no trm acquisition data  mc11b
mc11c 209 of  1046 Best =  51.424
skipping specimen -  no trm acquisition data  mc11c
skipping  mc11d  : no best 
mc11e 211 of  1046 Best =  30.31
skipping specimen -  no trm acquisition data  mc11e
skipping  mc11f  : no best 
skipping  mc11g  : no best 
mc11h 214 of  1046 Best =  22.828
skipping specimen -  no trm acquisition data  mc11h
mc120a1 215 of  1046 Best =  24.746
skipping specimen -  no trm acquisition data  mc120a1
skipping  mc120a2  : no best 
skipping  mc120a2-1  : no best 
mc120b1 218 of  1046 Best =  24.698999999999998
skipping specimen -  no trm acquisition data  mc120b1
mc120b2 219 of  1046 Best =  24.973
skipping specimen -  no trm acquisition data  mc120b2
mc120c1 220 of  1046 Best =  23.945
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 121
         Function evaluations: 227
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 46
         Function evaluations: 90
Banc=  23.934316018697352
1  saved in  mc120c1_TRM.png
mc120f1 221 of  1046 Best =  23.220000000000002
skipping specimen -  no trm acquisition data  mc120f1
skipping  mc120j2  : no best 
skipping  mc120l1  : no best 
skipping  mc120m2  : no best 
skipping  mc121a1  : no best 
mc121c1 226 of  1046 Best =  11.995
skipping specimen -  no trm acquisition data  mc121c1
skipping  mc121c3  : no best 
mc121d1 228 of  1046 Best =  24.039
skipping specimen -  no trm acquisition data  mc121d1
skipping  mc121d2  : no best 
mc121e1 230 of  1046 Best =  28.165
skipping specimen -  no trm acquisition data  mc121e1
skipping  mc121e2  : no best 
mc121f2 232 of  1046 Best =  20.479000000000003
skipping specimen -  no trm acquisition data  mc121f2
mc121g1 233 of  1046 Best =  34.742
skipping specimen -  no trm acquisition data  mc121g1
skipping  mc121i1  : no best 
mc121k1 235 of  1046 Best =  27.452
skipping specimen -  no trm acquisition data  mc121k1
mc121k2 236 of  1046 Best =  25.778
skipping specimen -  no trm acquisition data  mc121k2
skipping  mc122a1  : no best 
skipping  mc122b1  : no best 
skipping  mc122c1  : no best 
skipping  mc122d1  : no best 
skipping  mc122f1  : no best 
skipping  mc122g1  : no best 
skipping  mc122k2  : no best 
skipping  mc122l1  : no best 
skipping  mc123a1  : no best 
mc123a2 246 of  1046 Best =  33.027
skipping specimen -  no trm acquisition data  mc123a2
mc123b1 247 of  1046 Best =  27.64
skipping specimen -  no trm acquisition data  mc123b1
mc123b2 248 of  1046 Best =  30.2
skipping specimen -  no trm acquisition data  mc123b2
skipping  mc123c2  : no best 
mc123c3 250 of  1046 Best =  29.289
skipping specimen -  no trm acquisition data  mc123c3
skipping  mc123f1  : no best 
skipping  mc123j1  : no best 
mc124a1 253 of  1046 Best =  23.563000000000002
skipping specimen -  no trm acquisition data  mc124a1
skipping  mc124d1  : no best 
mc124d2 255 of  1046 Best =  19.270999999999997
skipping specimen -  no trm acquisition data  mc124d2
skipping  mc124f1  : no best 
skipping  mc124g1  : no best 
skipping  mc124h1  : no best 
skipping  mc124j1  : no best 
skipping  mc124l1  : no best 
skipping  mc125a1  : no best 
skipping  mc125b1  : no best 
skipping  mc125c1  : no best 
mc125d1 264 of  1046 Best =  6.071
skipping specimen -  no trm acquisition data  mc125d1
mc125e1 265 of  1046 Best =  5.1383
skipping specimen -  no trm acquisition data  mc125e1
skipping  mc125e3  : no best 
skipping  mc125g1  : no best 
mc125i1 268 of  1046 Best =  25.918000000000003
skipping specimen -  no trm acquisition data  mc125i1
skipping  mc125m1  : no best 
skipping  mc126a2  : no best 
skipping  mc126c1  : no best 
skipping  mc126c2  : no best 
skipping  mc126d1  : no best 
skipping  mc126e1  : no best 
skipping  mc126f1  : no best 
skipping  mc126g1  : no best 
skipping  mc126i1  : no best 
skipping  mc127a1  : no best 
mc127a2 279 of  1046 Best =  39.562
skipping specimen -  no trm acquisition data  mc127a2
skipping  mc127b1  : no best 
mc127c1 281 of  1046 Best =  37.410000000000004
skipping specimen -  no trm acquisition data  mc127c1
mc127d1 282 of  1046 Best =  36.535999999999994
skipping specimen -  no trm acquisition data  mc127d1
skipping  mc127f1  : no best 
skipping  mc127g2  : no best 
skipping  mc127i1  : no best 
skipping  mc128b1  : no best 
mc128b2 287 of  1046 Best =  32.681000000000004
skipping specimen -  no trm acquisition data  mc128b2
mc128c2 288 of  1046 Best =  37.394
skipping specimen -  no trm acquisition data  mc128c2
skipping  mc128d1  : no best 
skipping  mc128e1  : no best 
skipping  mc128e2  : no best 
skipping  mc128f1  : no best 
skipping  mc128h1  : no best 
mc128j1 294 of  1046 Best =  32.797
skipping specimen -  no trm acquisition data  mc128j1
skipping  mc129a1  : no best 
skipping  mc129a1-1  : no best 
skipping  mc129a2  : no best 
mc129b1 298 of  1046 Best =  49.913000000000004
skipping specimen -  no trm acquisition data  mc129b1
mc129c1 299 of  1046 Best =  48.964
skipping specimen -  no trm acquisition data  mc129c1
skipping  mc129c2  : no best 
skipping  mc129f1  : no best 
skipping  mc129h2  : no best 
skipping  mc129j1  : no best 
mc129l1 304 of  1046 Best =  18.143
skipping specimen -  no trm acquisition data  mc129l1
mc130a1 305 of  1046 Best =  29.331
skipping specimen -  no trm acquisition data  mc130a1
skipping  mc130a2  : no best 
skipping  mc130b1  : no best 
mc130d1 308 of  1046 Best =  21.107
skipping specimen -  no trm acquisition data  mc130d1
skipping  mc130e1  : no best 
skipping  mc130g2  : no best 
mc130h1 311 of  1046 Best =  17.167
skipping specimen -  no trm acquisition data  mc130h1
skipping  mc130i2  : no best 
skipping  mc130j2  : no best 
skipping  mc131a3  : no best 
mc131b1 315 of  1046 Best =  16.139
skipping specimen -  no trm acquisition data  mc131b1
mc131c2 316 of  1046 Best =  16.846
skipping specimen -  no trm acquisition data  mc131c2
mc131d2 317 of  1046 Best =  16.157
skipping specimen -  no trm acquisition data  mc131d2
mc131e1 318 of  1046 Best =  16.517000000000003
skipping specimen -  no trm acquisition data  mc131e1
skipping  mc131f1  : no best 
mc131g1 320 of  1046 Best =  18.297
skipping specimen -  no trm acquisition data  mc131g1
skipping  mc131k1  : no best 
skipping  mc132a1  : no best 
skipping  mc132c1  : no best 
skipping  mc132d1  : no best 
skipping  mc132e1  : no best 
mc132e2 326 of  1046 Best =  3.4638
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 96
         Function evaluations: 182
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 49
         Function evaluations: 92
Banc=  3.425136053903088
1  saved in  mc132e2_TRM.png
mc132f2 327 of  1046 Best =  3.269
skipping specimen -  no trm acquisition data  mc132f2
mc132g2 328 of  1046 Best =  3.2830000000000004
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 93
         Function evaluations: 174
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 48
         Function evaluations: 91
Banc=  3.255651982663153
1  saved in  mc132g2_TRM.png
mc132h2 329 of  1046 Best =  3.1635
skipping specimen -  no trm acquisition data  mc132h2
mc132i2 330 of  1046 Best =  3.4481
skipping specimen -  no trm acquisition data  mc132i2
mc132j1 331 of  1046 Best =  3.0716
skipping specimen -  no trm acquisition data  mc132j1
skipping  mc132j2  : no best 
mc132k1 333 of  1046 Best =  3.3592
skipping specimen -  no trm acquisition data  mc132k1
skipping  mc132l1  : no best 
skipping  mc133b2  : no best 
skipping  mc133d1  : no best 
mc133f1 337 of  1046 Best =  43.854
skipping specimen -  no trm acquisition data  mc133f1
skipping  mc133f2  : no best 
mc133g1 339 of  1046 Best =  48.738
skipping specimen -  no trm acquisition data  mc133g1
skipping  mc133h1  : no best 
skipping  mc133j1  : no best 
mc133l1 342 of  1046 Best =  47.263
skipping specimen -  no trm acquisition data  mc133l1
skipping  mc134a1  : no best 
skipping  mc134c1  : no best 
mc134c2 345 of  1046 Best =  18.596
skipping specimen -  no trm acquisition data  mc134c2
skipping  mc134e1  : no best 
mc134f1 347 of  1046 Best =  2.1912
skipping specimen -  no trm acquisition data  mc134f1
skipping  mc134k1  : no best 
mc135a1 349 of  1046 Best =  35.534
skipping specimen -  no trm acquisition data  mc135a1
skipping  mc135b1  : no best 
mc135c2 351 of  1046 Best =  41.081
skipping specimen -  no trm acquisition data  mc135c2
skipping  mc135d2  : no best 
mc135e1 353 of  1046 Best =  11.516
skipping specimen -  no trm acquisition data  mc135e1
skipping  mc135e2  : no best 
skipping  mc135h2  : no best 
skipping  mc135i2  : no best 
skipping  mc136a1  : no best 
mc136a2 358 of  1046 Best =  1.4154
skipping specimen -  no trm acquisition data  mc136a2
skipping  mc136c1  : no best 
skipping  mc136d1  : no best 
skipping  mc136d2  : no best 
skipping  mc136e1  : no best 
skipping  mc136g1  : no best 
skipping  mc136h2  : no best 
skipping  mc136i1  : no best 
skipping  mc136i2  : no best 
skipping  mc137a1  : no best 
skipping  mc137d1  : no best 
skipping  mc137h1  : no best 
skipping  mc137j2  : no best 
skipping  mc137l1  : no best 
skipping  mc138a1  : no best 
skipping  mc138b1  : no best 
skipping  mc138d1  : no best 
skipping  mc138g1  : no best 
skipping  mc138h1  : no best 
mc139a1 377 of  1046 Best =  5.361199999999999
skipping specimen -  no trm acquisition data  mc139a1
skipping  mc139a2  : no best 
mc139c1 379 of  1046 Best =  19.758999999999997
skipping specimen -  no trm acquisition data  mc139c1
skipping  mc139d1  : no best 
skipping  mc139e1  : no best 
skipping  mc139h1  : no best 
skipping  mc139j2  : no best 
mc13a 384 of  1046 Best =  28.479
skipping specimen -  no trm acquisition data  mc13a
mc13b 385 of  1046 Best =  29.978
skipping specimen -  no trm acquisition data  mc13b
mc13c 386 of  1046 Best =  32.768
skipping specimen -  no trm acquisition data  mc13c
mc13d 387 of  1046 Best =  31.644
skipping specimen -  no trm acquisition data  mc13d
skipping  mc13e  : no best 
skipping  mc13f  : no best 
skipping  mc13g  : no best 
skipping  mc13h  : no best 
mc140a1 392 of  1046 Best =  19.148999999999997
skipping specimen -  no trm acquisition data  mc140a1
mc140b1 393 of  1046 Best =  13.743
skipping specimen -  no trm acquisition data  mc140b1
mc140c1 394 of  1046 Best =  17.194
skipping specimen -  no trm acquisition data  mc140c1
mc140d1 395 of  1046 Best =  19.745
skipping specimen -  no trm acquisition data  mc140d1
skipping  mc140e1  : no best 
skipping  mc140g1  : no best 
skipping  mc140h1  : no best 
skipping  mc140j1  : no best 
skipping  mc141b1  : no best 
skipping  mc141b2  : no best 
skipping  mc141c1  : no best 
skipping  mc141g1  : no best 
skipping  mc141h3  : no best 
skipping  mc141k2  : no best 
skipping  mc141l1  : no best 
skipping  mc142b2  : no best 
mc142c1 408 of  1046 Best =  14.822
skipping specimen -  no trm acquisition data  mc142c1
skipping  mc142c2  : no best 
mc142d1 410 of  1046 Best =  13.381
skipping specimen -  no trm acquisition data  mc142d1
skipping  mc142e1  : no best 
mc142e2 412 of  1046 Best =  14.322
skipping specimen -  no trm acquisition data  mc142e2
mc142f2 413 of  1046 Best =  14.242
skipping specimen -  no trm acquisition data  mc142f2
skipping  mc142i2  : no best 
skipping  mc142k1  : no best 
mc142k2 416 of  1046 Best =  18.681
skipping specimen -  no trm acquisition data  mc142k2
skipping  mc143a1  : no best 
skipping  mc143b1  : no best 
skipping  mc143c1  : no best 
skipping  mc143d2  : no best 
skipping  mc143g1  : no best 
skipping  mc143h1  : no best 
skipping  mc143i1  : no best 
skipping  mc144a1  : no best 
skipping  mc144b1  : no best 
skipping  mc144d1  : no best 
mc144e1 427 of  1046 Best =  19.681
skipping specimen -  no trm acquisition data  mc144e1
mc144f1 428 of  1046 Best =  18.217
skipping specimen -  no trm acquisition data  mc144f1
mc144h1 429 of  1046 Best =  6.6641
skipping specimen -  no trm acquisition data  mc144h1
skipping  mc144h2  : no best 
skipping  mc144j1  : no best 
mc144j2 432 of  1046 Best =  19.352
skipping specimen -  no trm acquisition data  mc144j2
mc144k1 433 of  1046 Best =  12.438
skipping specimen -  no trm acquisition data  mc144k1
skipping  mc145b1  : no best 
skipping  mc145c1  : no best 
mc145c2 436 of  1046 Best =  6.683400000000001
skipping specimen -  no trm acquisition data  mc145c2
mc145f1 437 of  1046 Best =  7.2109
skipping specimen -  no trm acquisition data  mc145f1
skipping  mc145i1  : no best 
skipping  mc145j1  : no best 
mc145k2 440 of  1046 Best =  6.9291
skipping specimen -  no trm acquisition data  mc145k2
mc145l1 441 of  1046 Best =  6.9441
skipping specimen -  no trm acquisition data  mc145l1
skipping  mc146a1  : no best 
skipping  mc146d1  : no best 
mc146e1 444 of  1046 Best =  16.706
skipping specimen -  no trm acquisition data  mc146e1
mc146f1 445 of  1046 Best =  17.708000000000002
skipping specimen -  no trm acquisition data  mc146f1
skipping  mc146h1  : no best 
skipping  mc146i2  : no best 
skipping  mc146j1  : no best 
mc146j2 449 of  1046 Best =  6.4207
skipping specimen -  no trm acquisition data  mc146j2
skipping  mc146k1  : no best 
mc147a1 451 of  1046 Best =  26.443
skipping specimen -  no trm acquisition data  mc147a1
skipping  mc147c1  : no best 
mc147i1 453 of  1046 Best =  22.483
skipping specimen -  no trm acquisition data  mc147i1
mc147j2 454 of  1046 Best =  21.160999999999998
skipping specimen -  no trm acquisition data  mc147j2
mc147k2 455 of  1046 Best =  20.988
skipping specimen -  no trm acquisition data  mc147k2
skipping  mc148a1  : no best 
skipping  mc148b1  : no best 
skipping  mc148c1  : no best 
mc148d1 459 of  1046 Best =  53.363
skipping specimen -  no trm acquisition data  mc148d1
skipping  mc148f1  : no best 
mc148i1 461 of  1046 Best =  50.638
skipping specimen -  no trm acquisition data  mc148i1
mc148j1 462 of  1046 Best =  50.693
skipping specimen -  no trm acquisition data  mc148j1
skipping  mc148k1  : no best 
skipping  mc149a1  : no best 
skipping  mc149b1  : no best 
skipping  mc149d1  : no best 
skipping  mc149e1  : no best 
skipping  mc149g1  : no best 
skipping  mc14a  : no best 
mc14b 470 of  1046 Best =  70.667
skipping specimen -  no trm acquisition data  mc14b
mc14c 471 of  1046 Best =  39.543
skipping specimen -  no trm acquisition data  mc14c
mc14d 472 of  1046 Best =  54.568999999999996
skipping specimen -  no trm acquisition data  mc14d
skipping  mc14e  : no best 
skipping  mc14f  : no best 
skipping  mc14g  : no best 
mc14h 476 of  1046 Best =  83.116
skipping specimen -  no trm acquisition data  mc14h
skipping  mc150b1  : no best 
skipping  mc150c1  : no best 
skipping  mc150e1  : no best 
skipping  mc150f1  : no best 
skipping  mc150g1  : no best 
skipping  mc152a1  : no best 
skipping  mc152b1  : no best 
skipping  mc152b2  : no best 
skipping  mc152c1  : no best 
skipping  mc152e1  : no best 
skipping  mc152g1  : no best 
skipping  mc152i1  : no best 
skipping  mc152k1  : no best 
mc153a1 490 of  1046 Best =  29.753
skipping specimen -  no trm acquisition data  mc153a1
skipping  mc153a2  : no best 
mc153c1 492 of  1046 Best =  34.485
skipping specimen -  no trm acquisition data  mc153c1
skipping  mc153e1  : no best 
skipping  mc153i1  : no best 
skipping  mc153j1  : no best 
skipping  mc153m1  : no best 
skipping  mc154a1  : no best 
mc154a2 498 of  1046 Best =  8.6446
skipping specimen -  no trm acquisition data  mc154a2
skipping  mc154b1  : no best 
skipping  mc154e1  : no best 
skipping  mc154f1  : no best 
skipping  mc154h1  : no best 
mc154j2 503 of  1046 Best =  7.2961
skipping specimen -  no trm acquisition data  mc154j2
skipping  mc155a1  : no best 
skipping  mc155b1  : no best 
mc155c1 506 of  1046 Best =  34.239999999999995
skipping specimen -  no trm acquisition data  mc155c1
skipping  mc155e2  : no best 
skipping  mc155g1  : no best 
mc155h1 509 of  1046 Best =  26.489
skipping specimen -  no trm acquisition data  mc155h1
skipping  mc155i1  : no best 
mc155m1 511 of  1046 Best =  26.058999999999997
skipping specimen -  no trm acquisition data  mc155m1
skipping  mc156a1  : no best 
skipping  mc156b1  : no best 
skipping  mc156c1  : no best 
skipping  mc156c2  : no best 
skipping  mc156f1  : no best 
skipping  mc156g1  : no best 
skipping  mc156h1  : no best 
skipping  mc156i1  : no best 
skipping  mc157a1  : no best 
skipping  mc157a2  : no best 
skipping  mc157b1  : no best 
skipping  mc157b2  : no best 
mc157c2 524 of  1046 Best =  20.226
skipping specimen -  no trm acquisition data  mc157c2
skipping  mc157e2  : no best 
skipping  mc157f1  : no best 
skipping  mc157j1  : no best 
skipping  mc157k1  : no best 
mc158a1 529 of  1046 Best =  4.6788
skipping specimen -  no trm acquisition data  mc158a1
mc158b1 530 of  1046 Best =  4.5188
skipping specimen -  no trm acquisition data  mc158b1
skipping  mc158b2  : no best 
skipping  mc158c1  : no best 
skipping  mc158d1  : no best 
skipping  mc158f1  : no best 
skipping  mc158h1  : no best 
mc15a 536 of  1046 Best =  24.686
skipping specimen -  no trm acquisition data  mc15a
mc15b 537 of  1046 Best =  27.087
skipping specimen -  no trm acquisition data  mc15b
mc15c 538 of  1046 Best =  30.926999999999996
skipping specimen -  no trm acquisition data  mc15c
mc15c2 539 of  1046 Best =  29.088
skipping specimen -  no trm acquisition data  mc15c2
skipping  mc15d  : no best 
skipping  mc15e  : no best 
skipping  mc15f  : no best 
skipping  mc15g  : no best 
mc15h 544 of  1046 Best =  26.051
skipping specimen -  no trm acquisition data  mc15h
mc160a1 545 of  1046 Best =  20.888
skipping specimen -  no trm acquisition data  mc160a1
skipping  mc160a2  : no best 
skipping  mc160b1  : no best 
skipping  mc160c1  : no best 
mc160e1 549 of  1046 Best =  22.147
skipping specimen -  no trm acquisition data  mc160e1
skipping  mc160e2  : no best 
mc160f2 551 of  1046 Best =  22.721
skipping specimen -  no trm acquisition data  mc160f2
skipping  mc160h2  : no best 
skipping  mc160j1  : no best 
skipping  mc160j2  : no best 
skipping  mc161a1  : no best 
mc161b1 556 of  1046 Best =  5.8015
skipping specimen -  no trm acquisition data  mc161b1
skipping  mc161e1  : no best 
skipping  mc161f1  : no best 
mc161g1 559 of  1046 Best =  4.0994
skipping specimen -  no trm acquisition data  mc161g1
skipping  mc161j1  : no best 
skipping  mc161k1  : no best 
mc162b1 562 of  1046 Best =  7.2924
skipping specimen -  no trm acquisition data  mc162b1
skipping  mc162b2  : no best 
mc162c1 564 of  1046 Best =  8.4226
skipping specimen -  no trm acquisition data  mc162c1
skipping  mc162f1  : no best 
skipping  mc162g1  : no best 
skipping  mc162i1  : no best 
skipping  mc162j1  : no best 
skipping  mc163a1  : no best 
skipping  mc163b1  : no best 
skipping  mc163c1  : no best 
skipping  mc163d1  : no best 
skipping  mc163e1  : no best 
skipping  mc163f1  : no best 
skipping  mc163h1  : no best 
skipping  mc164a1  : no best 
skipping  mc164a2  : no best 
skipping  mc164a2-1  : no best 
skipping  mc164b1  : no best 
mc164c1 580 of  1046 Best =  81.363
skipping specimen -  no trm acquisition data  mc164c1
mc164f1 581 of  1046 Best =  81.241
skipping specimen -  no trm acquisition data  mc164f1
skipping  mc164g2  : no best 
skipping  mc164h1  : no best 
skipping  mc164i1  : no best 
mc164j1 585 of  1046 Best =  81.264
skipping specimen -  no trm acquisition data  mc164j1
skipping  mc164l2  : no best 
skipping  mc165a1  : no best 
mc165b1 588 of  1046 Best =  26.206
skipping specimen -  no trm acquisition data  mc165b1
skipping  mc165b2  : no best 
mc165c1 590 of  1046 Best =  24.218
skipping specimen -  no trm acquisition data  mc165c1
skipping  mc165c2  : no best 
skipping  mc165g1  : no best 
mc165h2 593 of  1046 Best =  26.373
skipping specimen -  no trm acquisition data  mc165h2
mc165i2 594 of  1046 Best =  28.343
skipping specimen -  no trm acquisition data  mc165i2
skipping  mc166a1  : no best 
mc166b1 596 of  1046 Best =  26.264000000000003
skipping specimen -  no trm acquisition data  mc166b1
skipping  mc166b2  : no best 
mc166c1 598 of  1046 Best =  21.977
skipping specimen -  no trm acquisition data  mc166c1
skipping  mc166c2  : no best 
mc166h2 600 of  1046 Best =  30.433
skipping specimen -  no trm acquisition data  mc166h2
skipping  mc166i1  : no best 
mc166i2 602 of  1046 Best =  37.746
skipping specimen -  no trm acquisition data  mc166i2
skipping  mc167a1  : no best 
mc167b1 604 of  1046 Best =  44.757
skipping specimen -  no trm acquisition data  mc167b1
mc167d2 605 of  1046 Best =  42.894
skipping specimen -  no trm acquisition data  mc167d2
skipping  mc167e1  : no best 
mc167e2 607 of  1046 Best =  42.548
skipping specimen -  no trm acquisition data  mc167e2
skipping  mc167f2  : no best 
skipping  mc167h1  : no best 
skipping  mc167j1  : no best 
mc167k1 611 of  1046 Best =  42.723
skipping specimen -  no trm acquisition data  mc167k1
mc168a1 612 of  1046 Best =  5.8325
skipping specimen -  no trm acquisition data  mc168a1
skipping  mc168c1  : no best 
mc168c2 614 of  1046 Best =  5.259200000000001
skipping specimen -  no trm acquisition data  mc168c2
mc168d1 615 of  1046 Best =  5.896
skipping specimen -  no trm acquisition data  mc168d1
mc168f1 616 of  1046 Best =  5.4868
skipping specimen -  no trm acquisition data  mc168f1
skipping  mc168h1  : no best 
mc168h2 618 of  1046 Best =  5.2021
skipping specimen -  no trm acquisition data  mc168h2
skipping  mc168i1  : no best 
skipping  mc168j1  : no best 
skipping  mc168k1  : no best 
skipping  mc170a1  : no best 
skipping  mc170c2  : no best 
skipping  mc170d1  : no best 
skipping  mc170e2  : no best 
skipping  mc170f1  : no best 
skipping  mc19a  : no best 
mc19b 628 of  1046 Best =  25.184
skipping specimen -  no trm acquisition data  mc19b
skipping  mc19c  : no best 
skipping  mc19d  : no best 
skipping  mc19e  : no best 
skipping  mc19f  : no best 
skipping  mc19g  : no best 
skipping  mc200a1  : no best 
skipping  mc200a2  : no best 
mc200b1 636 of  1046 Best =  15.245000000000001
skipping specimen -  no trm acquisition data  mc200b1
skipping  mc200b2  : no best 
mc200c1 638 of  1046 Best =  14.75
skipping specimen -  no trm acquisition data  mc200c1
skipping  mc200c2  : no best 
mc200d1 640 of  1046 Best =  11.645
skipping specimen -  no trm acquisition data  mc200d1
skipping  mc200d2  : no best 
mc200h1 642 of  1046 Best =  9.898299999999999
skipping specimen -  no trm acquisition data  mc200h1
mc200i1 643 of  1046 Best =  12.924
skipping specimen -  no trm acquisition data  mc200i1
skipping  mc201a1  : no best 
mc201b1 645 of  1046 Best =  4.6811
skipping specimen -  no trm acquisition data  mc201b1
skipping  mc201b2  : no best 
skipping  mc201c1  : no best 
skipping  mc201d1  : no best 
skipping  mc201e1  : no best 
skipping  mc201j1  : no best 
skipping  mc202a1  : no best 
mc202b1 652 of  1046 Best =  2.0582000000000003
skipping specimen -  no trm acquisition data  mc202b1
skipping  mc202c1  : no best 
skipping  mc202d1  : no best 
skipping  mc202f1  : no best 
skipping  mc202h1  : no best 
skipping  mc202j1  : no best 
skipping  mc203a1  : no best 
skipping  mc203b1  : no best 
skipping  mc203c1  : no best 
skipping  mc203d1  : no best 
skipping  mc203g1  : no best 
skipping  mc203h1  : no best 
skipping  mc204a1  : no best 
mc204b1 665 of  1046 Best =  21.512
skipping specimen -  no trm acquisition data  mc204b1
skipping  mc204c1  : no best 
skipping  mc204h1  : no best 
skipping  mc204k1  : no best 
skipping  mc204l1  : no best 
skipping  mc205a1  : no best 
skipping  mc205a1-1  : no best 
mc205a2 672 of  1046 Best =  43.245
skipping specimen -  no trm acquisition data  mc205a2
mc205b1 673 of  1046 Best =  30.262
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 119
         Function evaluations: 227
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 47
         Function evaluations: 90
Banc=  30.264922522967293
1  saved in  mc205b1_TRM.png
skipping  mc205c1  : no best 
skipping  mc205d1  : no best 
skipping  mc205e1  : no best 
mc205h1 677 of  1046 Best =  54.802
skipping specimen -  no trm acquisition data  mc205h1
skipping  mc205h2  : no best 
mc205i2 679 of  1046 Best =  46.272
skipping specimen -  no trm acquisition data  mc205i2
mc205k1 680 of  1046 Best =  57.307
skipping specimen -  no trm acquisition data  mc205k1
skipping  mc206a1  : no best 
mc206b1 682 of  1046 Best =  77.674
skipping specimen -  no trm acquisition data  mc206b1
mc206c1 683 of  1046 Best =  95.13000000000001
skipping specimen -  no trm acquisition data  mc206c1
mc206d1 684 of  1046 Best =  115.89
skipping specimen -  no trm acquisition data  mc206d1
mc206e1 685 of  1046 Best =  142.6
skipping specimen -  no trm acquisition data  mc206e1
mc206f1 686 of  1046 Best =  117.67
skipping specimen -  no trm acquisition data  mc206f1
skipping  mc206g1  : no best 
skipping  mc206h1  : no best 
skipping  mc206i1  : no best 
skipping  mc206k1  : no best 
skipping  mc207a1  : no best 
skipping  mc207b1  : no best 
skipping  mc207d1  : no best 
skipping  mc207g2  : no best 
skipping  mc207h2  : no best 
skipping  mc207k2  : no best 
skipping  mc208a1  : no best 
mc208b1 698 of  1046 Best =  22.966
skipping specimen -  no trm acquisition data  mc208b1
skipping  mc208c2  : no best 
skipping  mc208d2  : no best 
skipping  mc208e2  : no best 
skipping  mc208f2  : no best 
skipping  mc209a1  : no best 
skipping  mc209b1  : no best 
skipping  mc209b2  : no best 
skipping  mc209c2  : no best 
skipping  mc209e2  : no best 
skipping  mc209f1  : no best 
skipping  mc20a  : no best 
skipping  mc20b  : no best 
skipping  mc20c  : no best 
mc20d 712 of  1046 Best =  19.417
skipping specimen -  no trm acquisition data  mc20d
skipping  mc20e  : no best 
skipping  mc20f  : no best 
mc20h 715 of  1046 Best =  6.1885
skipping specimen -  no trm acquisition data  mc20h
skipping  mc210a2  : no best 
skipping  mc210b1  : no best 
skipping  mc210b2  : no best 
skipping  mc210c2  : no best 
skipping  mc210e1  : no best 
skipping  mc210i2  : no best 
skipping  mc211a1  : no best 
mc211b1 723 of  1046 Best =  96.82
skipping specimen -  no trm acquisition data  mc211b1
skipping  mc211b2  : no best 
mc211e1 725 of  1046 Best =  75.197
skipping specimen -  no trm acquisition data  mc211e1
skipping  mc211e2  : no best 
mc211g1 727 of  1046 Best =  73.62899999999999
skipping specimen -  no trm acquisition data  mc211g1
skipping  mc211g2  : no best 
mc211h1 729 of  1046 Best =  89.472
skipping specimen -  no trm acquisition data  mc211h1
mc211i1 730 of  1046 Best =  72.265
skipping specimen -  no trm acquisition data  mc211i1
skipping  mc212a1  : no best 
skipping  mc212b1  : no best 
skipping  mc212b2  : no best 
skipping  mc212c2  : no best 
skipping  mc212d2  : no best 
skipping  mc212g2  : no best 
skipping  mc213b1  : no best 
skipping  mc213e2  : no best 
skipping  mc213f2  : no best 
skipping  mc213g2  : no best 
skipping  mc213h2  : no best 
skipping  mc213i2  : no best 
skipping  mc214a2  : no best 
mc214b1 744 of  1046 Best =  48.841
skipping specimen -  no trm acquisition data  mc214b1
skipping  mc214b2  : no best 
mc214d1 746 of  1046 Best =  42.843
skipping specimen -  no trm acquisition data  mc214d1
skipping  mc214d2  : no best 
mc214g1 748 of  1046 Best =  43.812
skipping specimen -  no trm acquisition data  mc214g1
skipping  mc214g2  : no best 
mc214h1 750 of  1046 Best =  43.300000000000004
skipping specimen -  no trm acquisition data  mc214h1
mc214j1 751 of  1046 Best =  40.264
skipping specimen -  no trm acquisition data  mc214j1
skipping  mc214j2  : no best 
mc215a1 753 of  1046 Best =  51.161
skipping specimen -  no trm acquisition data  mc215a1
skipping  mc215a2  : no best 
mc215b1 755 of  1046 Best =  50.803000000000004
skipping specimen -  no trm acquisition data  mc215b1
mc215c1 756 of  1046 Best =  16.248
skipping specimen -  no trm acquisition data  mc215c1
skipping  mc215c2  : no best 
mc215d1 758 of  1046 Best =  11.825
skipping specimen -  no trm acquisition data  mc215d1
skipping  mc215d2  : no best 
mc215h1 760 of  1046 Best =  17.01
skipping specimen -  no trm acquisition data  mc215h1
skipping  mc215h2  : no best 
skipping  mc215i1  : no best 
mc216a1 763 of  1046 Best =  4.7359
skipping specimen -  no trm acquisition data  mc216a1
skipping  mc216a2  : no best 
mc216b1 765 of  1046 Best =  5.5174
skipping specimen -  no trm acquisition data  mc216b1
mc216c1 766 of  1046 Best =  4.2052
skipping specimen -  no trm acquisition data  mc216c1
skipping  mc216c2  : no best 
skipping  mc216f1  : no best 
skipping  mc216f2  : no best 
skipping  mc216g1  : no best 
skipping  mc216g2  : no best 
skipping  mc216h2  : no best 
mc217a1 773 of  1046 Best =  27.057
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 88
         Function evaluations: 169
Optimization terminated successfully.
         Current function value: 0.000000
         Iterations: 45
         Function evaluations: 88
Banc=  26.99010920060046
1  saved in  mc217a1_TRM.png
skipping  mc217a2  : no best 
skipping  mc217a2-1  : no best 
mc217b1 776 of  1046 Best =  25.301000000000002
skipping specimen -  no trm acquisition data  mc217b1
skipping  mc217b2  : no best 
mc217c1 778 of  1046 Best =  35.863
skipping specimen -  no trm acquisition data  mc217c1
skipping  mc217c2  : no best 
mc217d1 780 of  1046 Best =  28.92
skipping specimen -  no trm acquisition data  mc217d1
skipping  mc217d2  : no best 
mc217e1 782 of  1046 Best =  34.446000000000005
skipping specimen -  no trm acquisition data  mc217e1
skipping  mc217e2  : no best 
mc218a1 784 of  1046 Best =  36.967
skipping specimen -  no trm acquisition data  mc218a1
skipping  mc218a2  : no best 
mc218b1 786 of  1046 Best =  33.388
skipping specimen -  no trm acquisition data  mc218b1
skipping  mc218b2  : no best 
mc218d1 788 of  1046 Best =  35.802
skipping specimen -  no trm acquisition data  mc218d1
skipping  mc218d2  : no best 
mc218i1 790 of  1046 Best =  30.540000000000003
skipping specimen -  no trm acquisition data  mc218i1
skipping  mc218i2  : no best 
mc218j1 792 of  1046 Best =  34.821
skipping specimen -  no trm acquisition data  mc218j1
skipping  mc218j2  : no best 
mc219a1 794 of  1046 Best =  33.416
skipping specimen -  no trm acquisition data  mc219a1
skipping  mc219a2  : no best 
mc219b1 796 of  1046 Best =  34.7
skipping specimen -  no trm acquisition data  mc219b1
skipping  mc219b2  : no best 
mc219c1 798 of  1046 Best =  27.749000000000002
skipping specimen -  no trm acquisition data  mc219c1
skipping  mc219c2  : no best 
mc219d1 800 of  1046 Best =  26.239
skipping specimen -  no trm acquisition data  mc219d1
skipping  mc219d2  : no best 
mc219e1 802 of  1046 Best =  33.582
skipping specimen -  no trm acquisition data  mc219e1
skipping  mc219e2  : no best 
mc21a 804 of  1046 Best =  48.288000000000004
skipping specimen -  no trm acquisition data  mc21a
mc21b 805 of  1046 Best =  44.481
skipping specimen -  no trm acquisition data  mc21b
mc21c 806 of  1046 Best =  46.888999999999996
skipping specimen -  no trm acquisition data  mc21c
skipping  mc21d  : no best 
mc21e 808 of  1046 Best =  40.474
skipping specimen -  no trm acquisition data  mc21e
skipping  mc21f  : no best 
skipping  mc21g  : no best 
skipping  mc21h  : no best 
mc220a1 812 of  1046 Best =  54.211
skipping specimen -  no trm acquisition data  mc220a1
skipping  mc220a2  : no best 
mc220b1 814 of  1046 Best =  54.910000000000004
skipping specimen -  no trm acquisition data  mc220b1
skipping  mc220b2  : no best 
mc220c1 816 of  1046 Best =  52.954
skipping specimen -  no trm acquisition data  mc220c1
skipping  mc220c2  : no best 
mc220d1 818 of  1046 Best =  55.099000000000004
skipping specimen -  no trm acquisition data  mc220d1
skipping  mc220d2  : no best 
mc220e1 820 of  1046 Best =  52.783
skipping specimen -  no trm acquisition data  mc220e1
skipping  mc220f2  : no best 
skipping  mc221b1  : no best 
skipping  mc221c1  : no best 
skipping  mc221d2  : no best 
skipping  mc221h2  : no best 
skipping  mc221i2  : no best 
skipping  mc221j2  : no best 
skipping  mc222a1  : no best 
mc222b1 829 of  1046 Best =  12.673
skipping specimen -  no trm acquisition data  mc222b1
skipping  mc222c1  : no best 
skipping  mc222e1  : no best 
skipping  mc222h2  : no best 
skipping  mc222j2  : no best 
mc223a1 834 of  1046 Best =  21.524
skipping specimen -  no trm acquisition data  mc223a1
skipping  mc223a2  : no best 
mc223b1 836 of  1046 Best =  21.483999999999998
skipping specimen -  no trm acquisition data  mc223b1
skipping  mc223c1  : no best 
mc223c2 838 of  1046 Best =  24.791
skipping specimen -  no trm acquisition data  mc223c2
skipping  mc223d1  : no best 
skipping  mc223e1  : no best 
skipping  mc223f1  : no best 
mc223g1 842 of  1046 Best =  18.31
skipping specimen -  no trm acquisition data  mc223g1
mc223l1 843 of  1046 Best =  16.496
skipping specimen -  no trm acquisition data  mc223l1
skipping  mc224a1  : no best 
skipping  mc224b1  : no best 
skipping  mc224b2  : no best 
skipping  mc224c2  : no best 
skipping  mc224e2  : no best 
skipping  mc224f2  : no best 
mc225a1 850 of  1046 Best =  25.519000000000002
skipping specimen -  no trm acquisition data  mc225a1
skipping  mc225a2  : no best 
mc225b1 852 of  1046 Best =  25.846999999999998
skipping specimen -  no trm acquisition data  mc225b1
mc225c1 853 of  1046 Best =  25.956
skipping specimen -  no trm acquisition data  mc225c1
skipping  mc225c2  : no best 
mc225d1 855 of  1046 Best =  30.36
skipping specimen -  no trm acquisition data  mc225d1
skipping  mc225d2  : no best 
skipping  mc225f2  : no best 
skipping  mc225g2  : no best 
mc225i1 859 of  1046 Best =  32.043
skipping specimen -  no trm acquisition data  mc225i1
skipping  mc226a1  : no best 
mc226b1 861 of  1046 Best =  25.276999999999997
skipping specimen -  no trm acquisition data  mc226b1
skipping  mc226b2  : no best 
skipping  mc226d2  : no best 
skipping  mc226f2  : no best 
skipping  mc226g2  : no best 
mc227b1 866 of  1046 Best =  14.907
skipping specimen -  no trm acquisition data  mc227b1
skipping  mc227b2  : no best 
skipping  mc227c2  : no best 
skipping  mc227d2  : no best 
skipping  mc227f2  : no best 
skipping  mc227h2  : no best 
mc228a1 872 of  1046 Best =  10.568
skipping specimen -  no trm acquisition data  mc228a1
skipping  mc228a2  : no best 
mc228b1 874 of  1046 Best =  10.556000000000001
skipping specimen -  no trm acquisition data  mc228b1
skipping  mc228b2  : no best 
mc228d1 876 of  1046 Best =  13.165000000000001
skipping specimen -  no trm acquisition data  mc228d1
skipping  mc228d2  : no best 
mc228e1 878 of  1046 Best =  12.293000000000001
skipping specimen -  no trm acquisition data  mc228e1
skipping  mc228e2  : no best 
mc228g1 880 of  1046 Best =  17.339000000000002
skipping specimen -  no trm acquisition data  mc228g1
skipping  mc228g2  : no best 
skipping  mc229a2  : no best 
skipping  mc229b1  : no best 
skipping  mc229b2  : no best 
skipping  mc229e2  : no best 
mc229g1 886 of  1046 Best =  34.233000000000004
skipping specimen -  no trm acquisition data  mc229g1
skipping  mc229g2  : no best 
mc229h1 888 of  1046 Best =  26.781
skipping specimen -  no trm acquisition data  mc229h1
skipping  mc229h2  : no best 
mc229i1 890 of  1046 Best =  30.434
skipping specimen -  no trm acquisition data  mc229i1
mc229k1 891 of  1046 Best =  32.671
skipping specimen -  no trm acquisition data  mc229k1
mc26a 892 of  1046 Best =  38.491
skipping specimen -  no trm acquisition data  mc26a
skipping  mc26b  : no best 
mc26c 894 of  1046 Best =  22.822
skipping specimen -  no trm acquisition data  mc26c
mc26d 895 of  1046 Best =  32.531
skipping specimen -  no trm acquisition data  mc26d
mc26e 896 of  1046 Best =  58.436
skipping specimen -  no trm acquisition data  mc26e
skipping  mc26f  : no best 
skipping  mc26g  : no best 
skipping  mc26h  : no best 
mc28a 900 of  1046 Best =  27.106
skipping specimen -  no trm acquisition data  mc28a
mc28b 901 of  1046 Best =  12.902
skipping specimen -  no trm acquisition data  mc28b
mc28c 902 of  1046 Best =  25.694000000000003
skipping specimen -  no trm acquisition data  mc28c
skipping  mc28d  : no best 
skipping  mc28e  : no best 
mc28f 905 of  1046 Best =  29.26
skipping specimen -  no trm acquisition data  mc28f
skipping  mc28g  : no best 
skipping  mc28h  : no best 
skipping  mc29a  : no best 
skipping  mc29b  : no best 
skipping  mc29c  : no best 
mc29d 911 of  1046 Best =  30.445
skipping specimen -  no trm acquisition data  mc29d
skipping  mc29e  : no best 
skipping  mc29f  : no best 
skipping  mc29g  : no best 
skipping  mc29h  : no best 
mc30a 916 of  1046 Best =  42.782
skipping specimen -  no trm acquisition data  mc30a
mc30b 917 of  1046 Best =  42.202
skipping specimen -  no trm acquisition data  mc30b
skipping  mc30c  : no best 
mc30d 919 of  1046 Best =  42.455
skipping specimen -  no trm acquisition data  mc30d
mc30e 920 of  1046 Best =  43.085
skipping specimen -  no trm acquisition data  mc30e
skipping  mc30f  : no best 
skipping  mc30g  : no best 
skipping  mc30h  : no best 
mc31b 924 of  1046 Best =  14.018
skipping specimen -  no trm acquisition data  mc31b
skipping  mc31c  : no best 
skipping  mc31d  : no best 
skipping  mc31f  : no best 
skipping  mc31h  : no best 
mc32a 929 of  1046 Best =  29.437
skipping specimen -  no trm acquisition data  mc32a
mc32b 930 of  1046 Best =  32.111
skipping specimen -  no trm acquisition data  mc32b
skipping  mc32c  : no best 
mc32d 932 of  1046 Best =  39.678999999999995
skipping specimen -  no trm acquisition data  mc32d
mc32e 933 of  1046 Best =  28.057
skipping specimen -  no trm acquisition data  mc32e
skipping  mc32f  : no best 
skipping  mc32g  : no best 
skipping  mc32h  : no best 
skipping  mc33a  : no best 
mc33b 938 of  1046 Best =  37.315
skipping specimen -  no trm acquisition data  mc33b
mc33c 939 of  1046 Best =  32.118
skipping specimen -  no trm acquisition data  mc33c
skipping  mc33d  : no best 
mc33e 941 of  1046 Best =  32.316
skipping specimen -  no trm acquisition data  mc33e
skipping  mc33f  : no best 
skipping  mc33g  : no best 
skipping  mc33h  : no best 
skipping  mc34a  : no best 
skipping  mc34b  : no best 
mc34c 947 of  1046 Best =  23.047
skipping specimen -  no trm acquisition data  mc34c
skipping  mc34d  : no best 
skipping  mc34e  : no best 
skipping  mc34f  : no best 
skipping  mc34h  : no best 
mc35a 952 of  1046 Best =  23.831
skipping specimen -  no trm acquisition data  mc35a
mc35b 953 of  1046 Best =  22.151
skipping specimen -  no trm acquisition data  mc35b
mc35c 954 of  1046 Best =  23.294999999999998
skipping specimen -  no trm acquisition data  mc35c
mc35d 955 of  1046 Best =  26.063000000000002
skipping specimen -  no trm acquisition data  mc35d
skipping  mc35e  : no best 
skipping  mc35f  : no best 
skipping  mc35g  : no best 
skipping  mc35h  : no best 
mc36a 960 of  1046 Best =  29.828
skipping specimen -  no trm acquisition data  mc36a
mc36b 961 of  1046 Best =  25.085
skipping specimen -  no trm acquisition data  mc36b
skipping  mc36c  : no best 
skipping  mc36d  : no best 
mc36e 964 of  1046 Best =  22.808
skipping specimen -  no trm acquisition data  mc36e
skipping  mc36f  : no best 
skipping  mc36g  : no best 
mc36h 967 of  1046 Best =  25.029
skipping specimen -  no trm acquisition data  mc36h
skipping  mc37a  : no best 
skipping  mc37b  : no best 
mc37c 970 of  1046 Best =  62.835
skipping specimen -  no trm acquisition data  mc37c
mc37d 971 of  1046 Best =  52.525999999999996
skipping specimen -  no trm acquisition data  mc37d
mc37e 972 of  1046 Best =  62.544000000000004
skipping specimen -  no trm acquisition data  mc37e
skipping  mc37f  : no best 
skipping  mc37g  : no best 
mc37h 975 of  1046 Best =  63.644000000000005
skipping specimen -  no trm acquisition data  mc37h
skipping  mc38a  : no best 
skipping  mc38b  : no best 
skipping  mc38c  : no best 
skipping  mc38e  : no best 
skipping  mc38f  : no best 
mc38g 981 of  1046 Best =  28.373
skipping specimen -  no trm acquisition data  mc38g
skipping  mc38h  : no best 
mc39a 983 of  1046 Best =  25.953
skipping specimen -  no trm acquisition data  mc39a
mc39b 984 of  1046 Best =  33.651
skipping specimen -  no trm acquisition data  mc39b
mc39c 985 of  1046 Best =  22.065
skipping specimen -  no trm acquisition data  mc39c
skipping  mc39d  : no best 
skipping  mc39e  : no best 
skipping  mc39f  : no best 
skipping  mc39g  : no best 
skipping  mc39h  : no best 
skipping  mc40a  : no best 
skipping  mc40b  : no best 
skipping  mc40c  : no best 
mc40e 994 of  1046 Best =  39.356
skipping specimen -  no trm acquisition data  mc40e
skipping  mc40f  : no best 
skipping  mc40g  : no best 
skipping  mc40h  : no best 
skipping  mc41a  : no best 
skipping  mc41b  : no best 
skipping  mc41c  : no best 
skipping  mc41d  : no best 
skipping  mc41e  : no best 
skipping  mc41f  : no best 
skipping  mc41h  : no best 
skipping  mc42b  : no best 
skipping  mc42c  : no best 
skipping  mc42d  : no best 
skipping  mc42f  : no best 
skipping  mc42h  : no best 
skipping  mc43a  : no best 
skipping  mc43b  : no best 
skipping  mc43c  : no best 
skipping  mc43e  : no best 
mc43f 1014 of  1046 Best =  11.780999999999999
skipping specimen -  no trm acquisition data  mc43f
skipping  mc43g  : no best 
mc44a 1016 of  1046 Best =  32.555
skipping specimen -  no trm acquisition data  mc44a
mc44b 1017 of  1046 Best =  24.98
skipping specimen -  no trm acquisition data  mc44b
skipping  mc44c  : no best 
skipping  mc44d  : no best 
skipping  mc44e  : no best 
skipping  mc44f  : no best 
mc44g 1022 of  1046 Best =  12.024000000000001
skipping specimen -  no trm acquisition data  mc44g
mc44h 1023 of  1046 Best =  17.023
skipping specimen -  no trm acquisition data  mc44h
skipping  mc48a  : no best 
skipping  mc48b  : no best 
skipping  mc48c  : no best 
skipping  mc48d  : no best 
skipping  mc48e  : no best 
mc48f 1029 of  1046 Best =  15.402
skipping specimen -  no trm acquisition data  mc48f
mc48g 1030 of  1046 Best =  15.044
skipping specimen -  no trm acquisition data  mc48g
skipping  mc48h  : no best 
skipping  mc49a  : no best 
skipping  mc49b  : no best 
skipping  mc49c  : no best 
skipping  mc49d  : no best 
skipping  mc49e  : no best 
skipping  mc49g  : no best 
skipping  mc49h  : no best 
mc50a 1039 of  1046 Best =  35.747
skipping specimen -  no trm acquisition data  mc50a
mc50b 1040 of  1046 Best =  34.048
skipping specimen -  no trm acquisition data  mc50b
skipping  mc50c  : no best 
skipping  mc50d  : no best 
mc50e 1043 of  1046 Best =  33.958999999999996
skipping specimen -  no trm acquisition data  mc50e
mc50f 1044 of  1046 Best =  31.189999999999998
skipping specimen -  no trm acquisition data  mc50f
skipping  mc50g  : no best 
skipping  mc50h  : no best 
6  records written to file  NLT_specimens.txt
In [230]:
Image("mc117b1_TRM.png")
Out[230]:
In [231]:
!uniform.py -n 50
  165.8   -38.3
  107.7   -13.4
  299.1    26.5
   75.4     7.0
  203.5   -51.0
  194.5   -12.6
  233.3   -12.4
   34.7    18.4
   82.5   -34.1
  336.7    32.8
  266.0    46.7
  299.8    -2.1
  125.5   -39.6
  141.9    28.7
  305.8   -68.7
  160.7     8.9
   11.5     2.7
  297.3   -13.6
  318.7   -13.8
  356.3    55.9
  253.5   -66.0
  323.6    -5.3
   88.7   -65.5
  267.2    40.7
   69.5   -70.3
  264.7   -13.5
  254.4    -3.4
   98.7    11.9
   97.8    -2.9
   91.9    26.0
  123.2   -19.8
  218.7    -2.9
   87.5    20.4
    2.5   -30.8
   62.4   -13.9
  180.1    16.6
   12.1    37.3
  247.7    55.5
  109.0    86.4
  238.7   -61.0
   87.6   -87.8
  324.7    51.6
  358.2    44.2
  142.3   -72.4
  321.9   -31.0
  162.5   -47.1
  311.8    24.8
  334.5    29.4
   19.5   -32.9
  299.8    -9.3
In [232]:
!uniform.py -n 50 > data_files/uniform/uniform.out
!eqarea.py -f data_files/uniform/uniform.out -fmt png -sav
1  saved in  uniform_eq.png
In [233]:
Image(filename='uniform_eq.png')
Out[233]:

update_measurements.txt

This program has been superceded by Pmag GUI, so you should use that.

upload_magic.py

[notebook version]

program has been superceded by Pmag GUI, so you should use that.

utrecht_magic.py

[notebook version]

In [234]:
!utrecht_magic.py -f data_files/convert_2_magic/UTRECHT_magic/Utrecht_Example.af
-I- Using online data model
-I- Using online data model
adding measurement column to measurements table!
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 350 records written to measurements file
-I- overwriting /Users/nebula/Python/PmagPy/specimens.txt
-I- 25 records written to specimens file
-I- overwriting /Users/nebula/Python/PmagPy/samples.txt
-I- 3 records written to samples file
-I- overwriting /Users/nebula/Python/PmagPy/sites.txt
-I- 3 records written to sites file
-I- overwriting /Users/nebula/Python/PmagPy/locations.txt
-I- 1 records written to locations file
-I- overwriting /Users/nebula/Python/PmagPy/measurements.txt
-I- 350 records written to measurements file
In [235]:
!vdm_b.py -f data_files/vdm_b/vdm_b_example.dat
 3.300e-05
In [236]:
!cat data_files/b_vdm/b_vdm_example.dat
33 22

vector_mean.py

[notebook version]

In [237]:
!vector_mean.py -f data_files/vector_mean/vector_mean_example.dat
    1.3    49.6    2.289e+06 100
In [238]:
!vgp_di.py -f data_files/vgp_di/vgp_di_example.dat
  335.6    62.9

vgpmap_magic.py

[notebook version]

In [239]:
!vgpmap_magic.py -WD data_files/3_0/McMurdo -f sites.txt -crd g -prj ortho -eye 60 0  -sym ko 10 -fmt png -S -sav
-I- Using online data model
gridlines only supported for PlateCarree and Mercator plots currently
1  saved in  McMurdo_VGP_map.png
In [240]:
image = None
if cartopy_present:
    image = Image("McMurdo_VGP_map.png")
image
Out[240]:

vgpmap_magic2.py

In [241]:
# MagIC 2 version of vgpmap_magic.py
!vgpmap_magic2.py -f data_files/vgpmap_magic/pmag_results.txt \
    -crd g -prj ortho -eye 60 0 -etp -sym wo 10 -fmt png -sav
gridlines only supported for PlateCarree and Mercator plots currently
1  saved in  Snake_River_VGP_map.png
In [242]:
if cartopy_present:
    image = Image(filename='Snake_River_VGP_map.png')
else:
    image = None
image
Out[242]:

watsons_f.py

[notebook version]

In [243]:
!watsons_f.py -f data_files/watsons_f/watsons_f_example_file1.dat \
-f2 data_files/watsons_f/watsons_f_example_file2.dat
   5.23    3.26

watsons_v.py

[notebook version]

In [244]:
!watsons_v.py -f data_files/watsons_f/watsons_f_example_file1.dat \
-f2 data_files/watsons_f/watsons_f_example_file2.dat -fmt png -sav
Watson's V,  Vcrit: 
         10.5        6.4
1  saved in  watsons_v_watsons_f_example_file1_watsons_f_example_file2.png
In [245]:
Image(filename="watsons_v_watsons_f_example_file1_watsons_f_example_file2.png")
Out[245]:

zeq.py

[notebook version]

This program requires interaction and can only be run from the command line.

zeq_magic.py

[notebook version]

Note: This program is no longer maintained. It has been superceded by demag_gui.py
In [246]:
!zeq_magic.py -WD data_files/3_0/McMurdo -spc mc01a -fmt png
Image('mc01a_eqarea.png')
-I- Using online data model
mc01a 1 out of  1038
1  saved in  mc01a_eqarea.png
2  saved in  mc01a_zijd.png
3  saved in  mc01a_demag.png
Out[246]:

cleanup the directory

In [247]:
import os
import glob
import shutil


glob_list = ['data_files/irmaq_magic/*.magic', '*.magic', '*.png', '*.jpg',
            'data_files/convert_2_magic/mini_magic/s*.txt', 'data_files/convert_2_magic/s_magic/*.txt',
            'data_files/irmaq_magic/coil*.txt', 'rmag_*.txt', 'data_files/orientation_magic/s*.txt',
            'data_files/mk_redo/*redo*', 'data_files/nrm_specimens_magic/s*.txt', 'data_files/irmaq_magic/s*.txt',
            'data_files/download_magic/pmag_s*.txt', 'data_files/convert_2_magic/tdt_magic/*.txt']
for pattern in glob_list:
    for fname in glob.glob(pattern):
        os.remove(fname)
    
    
files_to_remove = ["data_files/aarm_magic/aarm_measurements.txt", "data_files/irmaq_magic/magic_measurements.txt",
                  "data_files/download_magic/er_ages.txt", "data_files/download_magic/er_citations.txt",
                  "data_files/azdip_magic/er_samples.txt", "data_files/azdip_magic/samples.txt",
                  "data_files/convert_2_magic/mini_magic/locations.txt", 
                  "data_files/convert_2_magic/mini_magic/measurements.txt", "measurements.txt", 'specimens.txt',
                  'sites.txt', 'locations.txt', 'stored.json', 'data_files/nrm_specimens_magic/criteria.txt',
                  'data_files/download_magic/er_locations.txt', 'data_files/download_magic/pmag_results.txt',
                  'data_files/nrm_specimens_magic/measurements.txt', 'data_files/nrm_specimens_magic/locations.txt',
                  'data_files/nrm_specimens_magic/contribution.txt', 'data_files/nrm_specimens_magic/ages.txt', 
                  'data_files/irmaq_magic/locations.txt', 'data_files/download_magic/specimens.txt', 
                  'data_files/download_magic/samples.txt', 'data_files/download_magic/locations.txt', 
                  'data_files/download_magic/contribution.txt', 'data_files/download_magic/criteria.txt',
                  'data_files/download_magic/ages.txt', 'data_files/download_magic/measurements.txt', 
                  'data_files/convert_2_magic/tdt_magic/custom.out', 'custom.txt', 
                  'data_files/convert_2_magic/huji_magic/specimens.txt', 
                  'data_files/convert_2_magic/huji_magic/locations.txt', 'data_files/aarm_magic/measurements.txt']
for fname in files_to_remove:
    try:
        os.remove(fname)
    except FileNotFoundError:
        pass
for dtype in ['specimens.txt', 'samples.txt', 'sites.txt', 'locations.txt']:
    try:
        os.remove(dtype)
    except FileNotFoundError:
        pass
    for fname in os.listdir():
        if fname.endswith(dtype):
            os.remove(fname)